From d9377f09e1d3e21754f346867598ab39b465e9fa Mon Sep 17 00:00:00 2001 From: William Levack Payne <108789355+WillLP-code@users.noreply.github.com> Date: Thu, 9 Nov 2023 11:46:56 +0000 Subject: [PATCH] ml forecast house prices --- .../data/1980 2023 average house prices.csv | 524 ++ .../forecasting tutorial.ipynb | 5458 ++++++++++++ ml-data science tutorials/logs.log | 7857 +++++++++++++++++ 3 files changed, 13839 insertions(+) create mode 100644 ml-data science tutorials/data/1980 2023 average house prices.csv create mode 100644 ml-data science tutorials/forecasting tutorial.ipynb create mode 100644 ml-data science tutorials/logs.log diff --git a/ml-data science tutorials/data/1980 2023 average house prices.csv b/ml-data science tutorials/data/1980 2023 average house prices.csv new file mode 100644 index 0000000..619a44a --- /dev/null +++ b/ml-data science tutorials/data/1980 2023 average house prices.csv @@ -0,0 +1,524 @@ +Name,Period,House price index All property types,Average price All property types,Percentage change (monthly) All property types,Percentage change (yearly) All property types +United Kingdom,1980-01,10.11,19273,3.94,28.59 +United Kingdom,1980-02,10.11,19273,3.94,28.59 +United Kingdom,1980-03,10.11,19273,3.94,28.59 +United Kingdom,1980-04,10.51,20044,4,24.15 +United Kingdom,1980-05,10.51,20044,4,24.15 +United Kingdom,1980-06,10.51,20044,4,24.15 +United Kingdom,1980-07,10.94,20857,4.05,19.98 +United Kingdom,1980-08,10.94,20857,4.05,19.98 +United Kingdom,1980-09,10.94,20857,4.05,19.98 +United Kingdom,1980-10,10.96,20897,0.19,12.71 +United Kingdom,1980-11,10.96,20897,0.19,12.71 +United Kingdom,1980-12,10.96,20897,0.19,12.71 +United Kingdom,1981-01,10.98,20938,0.19,8.64 +United Kingdom,1981-02,10.98,20938,0.19,8.64 +United Kingdom,1981-03,10.98,20938,0.19,8.64 +United Kingdom,1981-04,11.28,21507,2.72,7.29 +United Kingdom,1981-05,11.28,21507,2.72,7.29 +United Kingdom,1981-06,11.28,21507,2.72,7.29 +United Kingdom,1981-07,11.46,21852,1.61,4.77 +United Kingdom,1981-08,11.46,21852,1.61,4.77 +United Kingdom,1981-09,11.46,21852,1.61,4.77 +United Kingdom,1981-10,11.24,21425,-1.95,2.53 +United Kingdom,1981-11,11.24,21425,-1.95,2.53 +United Kingdom,1981-12,11.24,21425,-1.95,2.53 +United Kingdom,1982-01,10.96,20897,-2.46,-0.19 +United Kingdom,1982-02,10.96,20897,-2.46,-0.19 +United Kingdom,1982-03,10.96,20897,-2.46,-0.19 +United Kingdom,1982-04,11.44,21811,4.37,1.42 +United Kingdom,1982-05,11.44,21811,4.37,1.42 +United Kingdom,1982-06,11.44,21811,4.37,1.42 +United Kingdom,1982-07,11.73,22360,2.51,2.32 +United Kingdom,1982-08,11.73,22360,2.51,2.32 +United Kingdom,1982-09,11.73,22360,2.51,2.32 +United Kingdom,1982-10,11.9,22685,1.45,5.88 +United Kingdom,1982-11,11.9,22685,1.45,5.88 +United Kingdom,1982-12,11.9,22685,1.45,5.88 +United Kingdom,1983-01,12.25,23355,2.95,11.76 +United Kingdom,1983-02,12.25,23355,2.95,11.76 +United Kingdom,1983-03,12.25,23355,2.95,11.76 +United Kingdom,1983-04,12.68,24167,3.48,10.8 +United Kingdom,1983-05,12.68,24167,3.48,10.8 +United Kingdom,1983-06,12.68,24167,3.48,10.8 +United Kingdom,1983-07,13.21,25183,4.2,12.62 +United Kingdom,1983-08,13.21,25183,4.2,12.62 +United Kingdom,1983-09,13.21,25183,4.2,12.62 +United Kingdom,1983-10,13.31,25386,0.81,11.91 +United Kingdom,1983-11,13.31,25386,0.81,11.91 +United Kingdom,1983-12,13.31,25386,0.81,11.91 +United Kingdom,1984-01,13.42,25589,0.8,9.57 +United Kingdom,1984-02,13.42,25589,0.8,9.57 +United Kingdom,1984-03,13.42,25589,0.8,9.57 +United Kingdom,1984-04,13.85,26401,3.17,9.24 +United Kingdom,1984-05,13.85,26401,3.17,9.24 +United Kingdom,1984-06,13.85,26401,3.17,9.24 +United Kingdom,1984-07,14.38,27416,3.85,8.87 +United Kingdom,1984-08,14.38,27416,3.85,8.87 +United Kingdom,1984-09,14.38,27416,3.85,8.87 +United Kingdom,1984-10,14.59,27823,1.48,9.6 +United Kingdom,1984-11,14.59,27823,1.48,9.6 +United Kingdom,1984-12,14.59,27823,1.48,9.6 +United Kingdom,1985-01,14.59,27823,0,8.73 +United Kingdom,1985-02,14.59,27823,0,8.73 +United Kingdom,1985-03,14.59,27823,0,8.73 +United Kingdom,1985-04,15.12,28838,3.65,9.23 +United Kingdom,1985-05,15.12,28838,3.65,9.23 +United Kingdom,1985-06,15.12,28838,3.65,9.23 +United Kingdom,1985-07,15.44,29447,2.11,7.41 +United Kingdom,1985-08,15.44,29447,2.11,7.41 +United Kingdom,1985-09,15.44,29447,2.11,7.41 +United Kingdom,1985-10,15.98,30463,3.45,9.49 +United Kingdom,1985-11,15.98,30463,3.45,9.49 +United Kingdom,1985-12,15.98,30463,3.45,9.49 +United Kingdom,1986-01,16.3,31072,2,11.68 +United Kingdom,1986-02,16.3,31072,2,11.68 +United Kingdom,1986-03,16.3,31072,2,11.68 +United Kingdom,1986-04,17.04,32494,4.58,12.68 +United Kingdom,1986-05,17.04,32494,4.58,12.68 +United Kingdom,1986-06,17.04,32494,4.58,12.68 +United Kingdom,1986-07,17.79,33915,4.38,15.17 +United Kingdom,1986-08,17.79,33915,4.38,15.17 +United Kingdom,1986-09,17.79,33915,4.38,15.17 +United Kingdom,1986-10,18.32,34931,2.99,14.67 +United Kingdom,1986-11,18.32,34931,2.99,14.67 +United Kingdom,1986-12,18.32,34931,2.99,14.67 +United Kingdom,1987-01,18.85,35946,2.91,15.69 +United Kingdom,1987-02,18.85,35946,2.91,15.69 +United Kingdom,1987-03,18.85,35946,2.91,15.69 +United Kingdom,1987-04,19.71,37571,4.52,15.63 +United Kingdom,1987-05,19.71,37571,4.52,15.63 +United Kingdom,1987-06,19.71,37571,4.52,15.63 +United Kingdom,1987-07,20.66,39398,4.86,16.17 +United Kingdom,1987-08,20.66,39398,4.86,16.17 +United Kingdom,1987-09,20.66,39398,4.86,16.17 +United Kingdom,1987-10,21.89,41732,5.92,19.47 +United Kingdom,1987-11,21.89,41732,5.92,19.47 +United Kingdom,1987-12,21.89,41732,5.92,19.47 +United Kingdom,1988-01,22.81,43483,4.2,20.97 +United Kingdom,1988-02,22.81,43483,4.2,20.97 +United Kingdom,1988-03,22.81,43483,4.2,20.97 +United Kingdom,1988-04,24.18,46109,6.04,22.73 +United Kingdom,1988-05,24.18,46109,6.04,22.73 +United Kingdom,1988-06,24.18,46109,6.04,22.73 +United Kingdom,1988-07,27.4,52238,13.29,32.59 +United Kingdom,1988-08,27.4,52238,13.29,32.59 +United Kingdom,1988-09,27.4,52238,13.29,32.59 +United Kingdom,1988-10,29.08,55448,6.15,32.87 +United Kingdom,1988-11,29.08,55448,6.15,32.87 +United Kingdom,1988-12,29.08,55448,6.15,32.87 +United Kingdom,1989-01,29.69,56615,2.11,30.2 +United Kingdom,1989-02,29.69,56615,2.11,30.2 +United Kingdom,1989-03,29.69,56615,2.11,30.2 +United Kingdom,1989-04,30.76,58658,3.61,27.22 +United Kingdom,1989-05,30.76,58658,3.61,27.22 +United Kingdom,1989-06,30.76,58658,3.61,27.22 +United Kingdom,1989-07,31.84,60701,3.48,16.2 +United Kingdom,1989-08,31.84,60701,3.48,16.2 +United Kingdom,1989-09,31.84,60701,3.48,16.2 +United Kingdom,1989-10,31.22,59533,-1.92,7.37 +United Kingdom,1989-11,31.22,59533,-1.92,7.37 +United Kingdom,1989-12,31.22,59533,-1.92,7.37 +United Kingdom,1990-01,30.55,58250,-2.16,2.89 +United Kingdom,1990-02,30.55,58250,-2.16,2.89 +United Kingdom,1990-03,30.55,58250,-2.16,2.89 +United Kingdom,1990-04,30.28,57726,-0.9,-1.59 +United Kingdom,1990-05,30.28,57726,-0.9,-1.59 +United Kingdom,1990-06,30.28,57726,-0.9,-1.59 +United Kingdom,1990-07,30.83,58773,1.81,-3.18 +United Kingdom,1990-08,30.83,58773,1.81,-3.18 +United Kingdom,1990-09,30.83,58773,1.81,-3.18 +United Kingdom,1990-10,30.37,57901,-1.49,-2.74 +United Kingdom,1990-11,30.37,57901,-1.49,-2.74 +United Kingdom,1990-12,30.37,57901,-1.49,-2.74 +United Kingdom,1991-01,29.94,57086,-1.41,-2 +United Kingdom,1991-02,29.94,57086,-1.41,-2 +United Kingdom,1991-03,29.94,57086,-1.41,-2 +United Kingdom,1991-04,29.82,56853,-0.41,-1.51 +United Kingdom,1991-05,29.82,56853,-0.41,-1.51 +United Kingdom,1991-06,29.82,56853,-0.41,-1.51 +United Kingdom,1991-07,30.4,57959,1.94,-1.39 +United Kingdom,1991-08,30.4,57959,1.94,-1.39 +United Kingdom,1991-09,30.4,57959,1.94,-1.39 +United Kingdom,1991-10,30.12,57435,-0.9,-0.8 +United Kingdom,1991-11,30.12,57435,-0.9,-0.8 +United Kingdom,1991-12,30.12,57435,-0.9,-0.8 +United Kingdom,1992-01,29.64,56504,-1.62,-1.02 +United Kingdom,1992-02,29.64,56504,-1.62,-1.02 +United Kingdom,1992-03,29.64,56504,-1.62,-1.02 +United Kingdom,1992-04,28.93,55166,-2.37,-2.97 +United Kingdom,1992-05,28.93,55166,-2.37,-2.97 +United Kingdom,1992-06,28.93,55166,-2.37,-2.97 +United Kingdom,1992-07,29.02,55328,0.29,-4.54 +United Kingdom,1992-08,29.02,55328,0.29,-4.54 +United Kingdom,1992-09,29.02,55328,0.29,-4.54 +United Kingdom,1992-10,27.91,53213,-3.82,-7.35 +United Kingdom,1992-11,27.91,53213,-3.82,-7.35 +United Kingdom,1992-12,27.91,53213,-3.82,-7.35 +United Kingdom,1993-01,28.05,53484,0.51,-5.34 +United Kingdom,1993-02,28.05,53484,0.51,-5.34 +United Kingdom,1993-03,28.05,53484,0.51,-5.34 +United Kingdom,1993-04,28.28,53918,0.81,-2.26 +United Kingdom,1993-05,28.28,53918,0.81,-2.26 +United Kingdom,1993-06,28.28,53918,0.81,-2.26 +United Kingdom,1993-07,28.88,55057,2.11,-0.49 +United Kingdom,1993-08,28.88,55057,2.11,-0.49 +United Kingdom,1993-09,28.88,55057,2.11,-0.49 +United Kingdom,1993-10,28.34,54026,-1.87,1.53 +United Kingdom,1993-11,28.34,54026,-1.87,1.53 +United Kingdom,1993-12,28.34,54026,-1.87,1.53 +United Kingdom,1994-01,28.65,54623,1.1,2.13 +United Kingdom,1994-02,28.65,54623,1.1,2.13 +United Kingdom,1994-03,28.65,54623,1.1,2.13 +United Kingdom,1994-04,29.05,55383,1.39,2.72 +United Kingdom,1994-05,29.05,55383,1.39,2.72 +United Kingdom,1994-06,29.05,55383,1.39,2.72 +United Kingdom,1994-07,29.53,56305,1.67,2.27 +United Kingdom,1994-08,29.53,56305,1.67,2.27 +United Kingdom,1994-09,29.53,56305,1.67,2.27 +United Kingdom,1994-10,29.33,55925,-0.67,3.51 +United Kingdom,1994-11,29.33,55925,-0.67,3.51 +United Kingdom,1994-12,29.33,55925,-0.67,3.51 +United Kingdom,1995-01,29.08,55437,-0.87,1.49 +United Kingdom,1995-02,29.08,55437,-0.87,1.49 +United Kingdom,1995-03,29.08,55437,-0.87,1.49 +United Kingdom,1995-04,29.39,56033,1.08,1.18 +United Kingdom,1995-05,29.39,56033,1.08,1.18 +United Kingdom,1995-06,29.39,56033,1.08,1.18 +United Kingdom,1995-07,29.64,56522,0.87,0.39 +United Kingdom,1995-08,29.64,56522,0.87,0.39 +United Kingdom,1995-09,29.64,56522,0.87,0.39 +United Kingdom,1995-10,29.25,55762,-1.34,-0.29 +United Kingdom,1995-11,29.25,55762,-1.34,-0.29 +United Kingdom,1995-12,29.25,55762,-1.34,-0.29 +United Kingdom,1996-01,29.67,56576,1.46,2.05 +United Kingdom,1996-02,29.67,56576,1.46,2.05 +United Kingdom,1996-03,29.67,56576,1.46,2.05 +United Kingdom,1996-04,29.7,56630,0.1,1.06 +United Kingdom,1996-05,29.7,56630,0.1,1.06 +United Kingdom,1996-06,29.7,56630,0.1,1.06 +United Kingdom,1996-07,30.87,58854,3.93,4.13 +United Kingdom,1996-08,30.87,58854,3.93,4.13 +United Kingdom,1996-09,30.87,58854,3.93,4.13 +United Kingdom,1996-10,31.41,59885,1.75,7.39 +United Kingdom,1996-11,31.41,59885,1.75,7.39 +United Kingdom,1996-12,31.41,59885,1.75,7.39 +United Kingdom,1997-01,31.84,60698,1.36,7.29 +United Kingdom,1997-02,31.84,60698,1.36,7.29 +United Kingdom,1997-03,31.84,60698,1.36,7.29 +United Kingdom,1997-04,32.49,61946,2.06,9.39 +United Kingdom,1997-05,32.49,61946,2.06,9.39 +United Kingdom,1997-06,32.49,61946,2.06,9.39 +United Kingdom,1997-07,34.14,65092,5.08,10.6 +United Kingdom,1997-08,34.14,65092,5.08,10.6 +United Kingdom,1997-09,34.14,65092,5.08,10.6 +United Kingdom,1997-10,33.88,64604,-0.75,7.88 +United Kingdom,1997-11,33.88,64604,-0.75,7.88 +United Kingdom,1997-12,33.88,64604,-0.75,7.88 +United Kingdom,1998-01,34.74,66231,2.52,9.12 +United Kingdom,1998-02,34.74,66231,2.52,9.12 +United Kingdom,1998-03,34.74,66231,2.52,9.12 +United Kingdom,1998-04,36.59,69757,5.32,12.61 +United Kingdom,1998-05,36.59,69757,5.32,12.61 +United Kingdom,1998-06,36.59,69757,5.32,12.61 +United Kingdom,1998-07,38.18,72795,4.35,11.83 +United Kingdom,1998-08,38.18,72795,4.35,11.83 +United Kingdom,1998-09,38.18,72795,4.35,11.83 +United Kingdom,1998-10,38.01,72469,-0.45,12.17 +United Kingdom,1998-11,38.01,72469,-0.45,12.17 +United Kingdom,1998-12,38.01,72469,-0.45,12.17 +United Kingdom,1999-01,38.24,72903,0.6,10.07 +United Kingdom,1999-02,38.24,72903,0.6,10.07 +United Kingdom,1999-03,38.24,72903,0.6,10.07 +United Kingdom,1999-04,39.86,75995,4.24,8.94 +United Kingdom,1999-05,39.86,75995,4.24,8.94 +United Kingdom,1999-06,39.86,75995,4.24,8.94 +United Kingdom,1999-07,42.19,80443,5.85,10.51 +United Kingdom,1999-08,42.19,80443,5.85,10.51 +United Kingdom,1999-09,42.19,80443,5.85,10.51 +United Kingdom,1999-10,43.27,82504,2.56,13.85 +United Kingdom,1999-11,43.27,82504,2.56,13.85 +United Kingdom,1999-12,43.27,82504,2.56,13.85 +United Kingdom,2000-01,44.38,84620,2.56,16.07 +United Kingdom,2000-02,44.38,84620,2.56,16.07 +United Kingdom,2000-03,44.38,84620,2.56,16.07 +United Kingdom,2000-04,46.8,89230,5.45,17.42 +United Kingdom,2000-05,46.8,89230,5.45,17.42 +United Kingdom,2000-06,46.8,89230,5.45,17.42 +United Kingdom,2000-07,47.68,90912,1.88,13.01 +United Kingdom,2000-08,47.68,90912,1.88,13.01 +United Kingdom,2000-09,47.68,90912,1.88,13.01 +United Kingdom,2000-10,49.1,93624,2.98,13.48 +United Kingdom,2000-11,49.1,93624,2.98,13.48 +United Kingdom,2000-12,49.1,93624,2.98,13.48 +United Kingdom,2001-01,48.85,93136,-0.52,10.06 +United Kingdom,2001-02,48.85,93136,-0.52,10.06 +United Kingdom,2001-03,48.85,93136,-0.52,10.06 +United Kingdom,2001-04,50.61,96499,3.61,8.15 +United Kingdom,2001-05,50.61,96499,3.61,8.15 +United Kingdom,2001-06,50.61,96499,3.61,8.15 +United Kingdom,2001-07,52.43,99971,3.6,9.96 +United Kingdom,2001-08,52.43,99971,3.6,9.96 +United Kingdom,2001-09,52.43,99971,3.6,9.96 +United Kingdom,2001-10,51.38,97964,-2.01,4.63 +United Kingdom,2001-11,51.38,97964,-2.01,4.63 +United Kingdom,2001-12,51.38,97964,-2.01,4.63 +United Kingdom,2002-01,51.2,97623,-0.35,4.82 +United Kingdom,2002-02,53.06,101164,3.63,8.62 +United Kingdom,2002-03,54.92,104705,3.5,12.42 +United Kingdom,2002-04,55.66,106121,1.35,9.97 +United Kingdom,2002-05,57.09,108852,2.57,12.8 +United Kingdom,2002-06,59.43,113304,4.09,17.41 +United Kingdom,2002-07,59.9,114214,0.8,14.25 +United Kingdom,2002-08,61.23,116743,2.21,16.78 +United Kingdom,2002-09,62.72,119576,2.43,19.61 +United Kingdom,2002-10,63.19,120486,0.76,22.99 +United Kingdom,2002-11,63.83,121700,1.01,24.23 +United Kingdom,2002-12,65.95,125747,3.33,28.36 +United Kingdom,2003-01,65.47,124836,-0.72,27.88 +United Kingdom,2003-02,64.78,123521,-1.05,22.1 +United Kingdom,2003-03,66.16,126152,2.13,20.48 +United Kingdom,2003-04,67.76,129186,2.41,21.73 +United Kingdom,2003-05,67.28,128276,-0.7,17.84 +United Kingdom,2003-06,67.44,128579,0.24,13.48 +United Kingdom,2003-07,68.6,130805,1.73,14.53 +United Kingdom,2003-08,69.83,133132,1.78,14.04 +United Kingdom,2003-09,69.61,132727,-0.3,11 +United Kingdom,2003-10,70.83,135054,1.75,12.09 +United Kingdom,2003-11,70.04,133536,-1.12,9.73 +United Kingdom,2003-12,71.42,136167,1.97,8.29 +United Kingdom,2004-01,71.84,136976,0.59,9.72 +United Kingdom,2004-02,71.15,135661,-0.96,9.83 +United Kingdom,2004-03,71.31,135964,0.22,7.78 +United Kingdom,2004-04,74.55,142135,4.54,10.02 +United Kingdom,2004-05,75.45,143855,1.21,12.15 +United Kingdom,2004-06,76.78,146384,1.76,13.85 +United Kingdom,2004-07,78.42,149520,2.14,14.31 +United Kingdom,2004-08,79.32,151240,1.15,13.6 +United Kingdom,2004-09,79.16,150937,-0.2,13.72 +United Kingdom,2004-10,79.75,152050,0.74,12.58 +United Kingdom,2004-11,79.64,151847,-0.13,13.71 +United Kingdom,2004-12,79.06,150734,-0.73,10.7 +United Kingdom,2005-01,79,150633,-0.07,9.97 +United Kingdom,2005-02,78.93,150488,-0.1,10.93 +United Kingdom,2005-03,79.58,151723,0.82,11.59 +United Kingdom,2005-04,80.71,153880,1.42,8.26 +United Kingdom,2005-05,81.57,155533,1.07,8.12 +United Kingdom,2005-06,82.22,156767,0.79,7.09 +United Kingdom,2005-07,83.28,158786,1.29,6.2 +United Kingdom,2005-08,83.62,159431,0.41,5.42 +United Kingdom,2005-09,83.49,159183,-0.16,5.46 +United Kingdom,2005-10,83.32,158865,-0.2,4.48 +United Kingdom,2005-11,83.57,159337,0.3,4.93 +United Kingdom,2005-12,84.03,160209,0.55,6.29 +United Kingdom,2006-01,83.9,159970,-0.15,6.2 +United Kingdom,2006-02,84.04,160231,0.16,6.47 +United Kingdom,2006-03,84.72,161531,0.81,6.46 +United Kingdom,2006-04,86.56,165042,2.17,7.25 +United Kingdom,2006-05,87.38,166606,0.95,7.12 +United Kingdom,2006-06,88.21,168184,0.95,7.28 +United Kingdom,2006-07,89.48,170604,1.44,7.44 +United Kingdom,2006-08,90.23,172037,0.84,7.91 +United Kingdom,2006-09,90.6,172738,0.41,8.52 +United Kingdom,2006-10,91.13,173750,0.59,9.37 +United Kingdom,2006-11,91.6,174644,0.51,9.61 +United Kingdom,2006-12,92.74,176819,1.25,10.37 +United Kingdom,2007-01,92.71,176758,-0.03,10.49 +United Kingdom,2007-02,92.97,177261,0.28,10.63 +United Kingdom,2007-03,93.69,178636,0.78,10.59 +United Kingdom,2007-04,95.58,182243,2.02,10.42 +United Kingdom,2007-05,96.68,184330,1.15,10.64 +United Kingdom,2007-06,97.74,186348,1.09,10.8 +United Kingdom,2007-07,98.96,188691,1.26,10.6 +United Kingdom,2007-08,99.54,189786,0.58,10.32 +United Kingdom,2007-09,99.67,190032,0.13,10.01 +United Kingdom,2007-10,99.44,189589,-0.23,9.12 +United Kingdom,2007-11,99.38,189489,-0.05,8.5 +United 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Kingdom,2014-11,100.29,191209,-0.34,8.43 +United Kingdom,2014-12,100.53,191669,0.24,7.7 +United Kingdom,2015-01,100,190665,-0.52,7.01 +United Kingdom,2015-02,100.09,190827,0.09,6.65 +United Kingdom,2015-03,100.46,191537,0.37,6.68 +United Kingdom,2015-04,101.34,193225,0.88,5.28 +United Kingdom,2015-05,102.44,195313,1.08,5.3 +United Kingdom,2015-06,103.22,196802,0.76,5.2 +United Kingdom,2015-07,104.97,200142,1.7,5.5 +United Kingdom,2015-08,105.93,201973,0.92,5.23 +United Kingdom,2015-09,106.15,202389,0.21,5.34 +United Kingdom,2015-10,106.29,202664,0.14,5.63 +United Kingdom,2015-11,107.11,204223,0.77,6.81 +United Kingdom,2015-12,107.48,204920,0.34,6.91 +United Kingdom,2016-01,107.76,205464,0.27,7.76 +United Kingdom,2016-02,107.81,205555,0.04,7.72 +United Kingdom,2016-03,108.92,207667,1.03,8.42 +United Kingdom,2016-04,109.32,208443,0.37,7.88 +United Kingdom,2016-05,110.6,210872,1.17,7.97 +United Kingdom,2016-06,111.65,212887,0.96,8.17 +United Kingdom,2016-07,112.83,215127,1.05,7.49 +United 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Kingdom,2018-04,118.49,225910,0.96,3.32 +United Kingdom,2018-05,118.97,226834,0.41,3.13 +United Kingdom,2018-06,119.77,228355,0.67,2.94 +United Kingdom,2018-07,121.25,231187,1.24,2.88 +United Kingdom,2018-08,121.63,231898,0.31,2.73 +United Kingdom,2018-09,121.39,231454,-0.19,2.92 +United Kingdom,2018-10,121.27,231211,-0.1,2.72 +United Kingdom,2018-11,120.75,230224,-0.43,2.57 +United Kingdom,2018-12,120.49,229729,-0.22,1.95 +United Kingdom,2019-01,119.75,228314,-0.62,1.68 +United Kingdom,2019-02,119.44,227738,-0.25,1.16 +United Kingdom,2019-03,119.11,227104,-0.28,1.49 +United Kingdom,2019-04,119.97,228749,0.72,1.26 +United Kingdom,2019-05,120.14,229061,0.14,0.98 +United Kingdom,2019-06,120.66,230049,0.43,0.74 +United Kingdom,2019-07,122,232618,1.12,0.62 +United Kingdom,2019-08,122.4,233366,0.32,0.63 +United Kingdom,2019-09,122.49,233536,0.07,0.9 +United Kingdom,2019-10,122.16,232919,-0.26,0.74 +United Kingdom,2019-11,121.73,232096,-0.35,0.81 +United Kingdom,2019-12,121.57,231792,-0.13,0.9 +United Kingdom,2020-01,121.65,231940,0.06,1.59 +United Kingdom,2020-02,120.95,230609,-0.57,1.26 +United Kingdom,2020-03,122.04,232684,0.9,2.46 +United Kingdom,2020-04,120.8,230318,-1.02,0.69 +United Kingdom,2020-05,121.42,231508,0.52,1.07 +United Kingdom,2020-06,123.1,234703,1.38,2.02 +United Kingdom,2020-07,124.14,236687,0.85,1.75 +United Kingdom,2020-08,125.35,238998,0.98,2.41 +United Kingdom,2020-09,126.68,241541,1.06,3.43 +United Kingdom,2020-10,127.75,243575,0.84,4.58 +United Kingdom,2020-11,129.06,246065,1.02,6.02 +United Kingdom,2020-12,130.06,247983,0.78,6.99 +United Kingdom,2021-01,130.96,249690,0.69,7.65 +United Kingdom,2021-02,130.9,249586,-0.04,8.23 +United Kingdom,2021-03,132.96,253506,1.57,8.95 +United Kingdom,2021-04,131.23,250210,-1.3,8.64 +United Kingdom,2021-05,131.79,251285,0.43,8.54 +United Kingdom,2021-06,139.34,265676,5.73,13.2 +United Kingdom,2021-07,132.67,252960,-4.79,6.88 +United Kingdom,2021-08,136.59,260429,2.95,8.97 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Kingdom,2023-06,151.2,288281,1.1,1.9 +United Kingdom,2023-07,152,289824,0.5,0.6 diff --git a/ml-data science tutorials/forecasting tutorial.ipynb b/ml-data science tutorials/forecasting tutorial.ipynb new file mode 100644 index 0000000..d8c7c0e --- /dev/null +++ b/ml-data science tutorials/forecasting tutorial.ipynb @@ -0,0 +1,5458 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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NamePeriodHouse price index All property typesAverage price All property typesPercentage change (monthly) All property typesPercentage change (yearly) All property typesMonthYearSeries
0United Kingdom1980-01-0110.11192733.9428.59119801
1United Kingdom1980-02-0110.11192733.9428.59219802
2United Kingdom1980-03-0110.11192733.9428.59319803
3United Kingdom1980-04-0110.51200444.0024.15419804
4United Kingdom1980-05-0110.51200444.0024.15519805
..............................
518United Kingdom2023-03-01148.20282548-1.003.2032023519
519United Kingdom2023-04-01148.902838710.502.5042023520
520United Kingdom2023-05-01149.502850530.401.6052023521
521United Kingdom2023-06-01151.202882811.101.9062023522
522United Kingdom2023-07-01152.002898240.500.6072023523
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523 rows × 9 columns

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" + ], + "text/plain": [ + " Name Period House price index All property types \\\n", + "0 United Kingdom 1980-01-01 10.11 \n", + "1 United Kingdom 1980-02-01 10.11 \n", + "2 United Kingdom 1980-03-01 10.11 \n", + "3 United Kingdom 1980-04-01 10.51 \n", + "4 United Kingdom 1980-05-01 10.51 \n", + ".. ... ... ... \n", + "518 United Kingdom 2023-03-01 148.20 \n", + "519 United Kingdom 2023-04-01 148.90 \n", + "520 United Kingdom 2023-05-01 149.50 \n", + "521 United Kingdom 2023-06-01 151.20 \n", + "522 United Kingdom 2023-07-01 152.00 \n", + "\n", + " Average price All property types \\\n", + "0 19273 \n", + "1 19273 \n", + "2 19273 \n", + "3 20044 \n", + "4 20044 \n", + ".. ... \n", + "518 282548 \n", + "519 283871 \n", + "520 285053 \n", + "521 288281 \n", + "522 289824 \n", + "\n", + " Percentage change (monthly) All property types \\\n", + "0 3.94 \n", + "1 3.94 \n", + "2 3.94 \n", + "3 4.00 \n", + "4 4.00 \n", + ".. ... \n", + "518 -1.00 \n", + "519 0.50 \n", + "520 0.40 \n", + "521 1.10 \n", + "522 0.50 \n", + "\n", + " Percentage change (yearly) All property types Month Year Series \n", + "0 28.59 1 1980 1 \n", + "1 28.59 2 1980 2 \n", + "2 28.59 3 1980 3 \n", + "3 24.15 4 1980 4 \n", + "4 24.15 5 1980 5 \n", + ".. ... ... ... ... \n", + "518 3.20 3 2023 519 \n", + "519 2.50 4 2023 520 \n", + "520 1.60 5 2023 521 \n", + "521 1.90 6 2023 522 \n", + "522 0.60 7 2023 523 \n", + "\n", + "[523 rows x 9 columns]" + ] + }, + "execution_count": 102, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# choose python 3.8 conda env\n", + "# pip install pycaret\n", + "from pycaret.regression import *\n", + "import pandas as pd\n", + "import numpy as np\n", + "\n", + "df = pd.read_csv('/workspaces/D2I-Jupyter-Notebook-Tools/ml-data science tutorials/data/1980 2023 average house prices.csv')\n", + "df['Period'] = pd.to_datetime(df['Period'], format='%Y-%m')\n", + "df['Month'] = [i.month for i in df['Period']]\n", + "df['Year'] = [i.year for i in df['Period']]\n", + "\n", + "df['Series'] = np.arange(1, len(df)+1)\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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SeriesYearMonthAverage price All property types
011980119273
121980219273
231980319273
341980420044
451980520044
...............
51851920233282548
51952020234283871
52052120235285053
52152220236288281
52252320237289824
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 DescriptionValue
0Session id123
1TargetAverage price All property types
2Target typeRegression
3Original data shape(372, 4)
4Transformed data shape(372, 4)
5Transformed train set shape(260, 4)
6Transformed test set shape(112, 4)
7Numeric features1
8PreprocessTrue
9Imputation typesimple
10Numeric imputationmean
11Categorical imputationmode
12Transform targetTrue
13Transform target methodyeo-johnson
14Fold GeneratorTimeSeriesSplit
15Fold Number3
16CPU Jobs-1
17Use GPUFalse
18Log ExperimentFalse
19Experiment Namereg-default-name
20USIc357
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 ModelMAEMSERMSER2RMSLEMAPETT (Sec)
huberHuber Regressor401.4442730330.6695493.4000-342.75220.03030.02490.0400
brBayesian Ridge406.7168637178.7544460.8611-361.67910.02960.02650.0267
lrLinear Regression406.8419636100.1089460.4708-361.99670.02960.02650.6500
enElastic Net406.8625636242.5939460.5224-414.89650.02960.02650.0233
ridgeRidge Regression406.8740636153.6122460.4902-361.67170.02960.02650.0367
larLeast Angle Regression406.8742636152.6535460.4898-367.62390.02960.02650.0267
lassoLasso Regression406.8759636150.7158460.4891-414.89650.02960.02650.0267
llarLasso Least Angle Regression406.8759636150.7537460.4892-414.89650.02960.02650.0267
ompOrthogonal Matching Pursuit407.1799635667.6341460.3143-362.41920.02960.02660.0300
parPassive Aggressive Regressor513.08881381573.6220678.6823-5137734055422490.00000.07780.11710.0267
dtDecision Tree Regressor1104.24525360442.31421336.7177-6.44360.09090.06590.0333
etExtra Trees Regressor1108.94595391101.32631340.5349-4.99370.09130.06620.1200
gbrGradient Boosting Regressor1109.86625395167.68101341.0404-7.12370.09130.06630.0533
rfRandom Forest Regressor1114.28305425661.65771344.8249-7.45670.09160.06650.1933
knnK Neighbors Regressor1124.51965492675.85711353.1046-3.59280.09230.06720.0400
lightgbmLight Gradient Boosting Machine1130.72615534960.47281358.3029-5.67430.09280.06760.2033
adaAdaBoost Regressor1209.55286091424.03501424.9473-6.56240.09850.07280.0500
dummyDummy Regressor2064.131314484283.57802197.2926-417.60800.17410.12940.0267
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MonthYearSeries
012010360
122010361
232010362
342010363
452010364
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MonthYearSeriesprediction_label
012010360125184.525406
122010361125634.533246
232010362126085.298396
342010363126536.820687
452010364126989.099952
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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import plotly.express as px\n", + "concat_df = pd.concat([df[df['Year'] < 2010],predictions_future], axis=0)\n", + "\n", + "fig = px.line(concat_df, x=concat_df['Series'], y=[\"Average price All property types\", \"prediction_label\"], template = 'plotly_dark')\n", + "fig.add_scatter(x=df['Series'], y=df['Average price All property types'])\n", + "\n", + "fig.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.18" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/ml-data science tutorials/logs.log b/ml-data science tutorials/logs.log new file mode 100644 index 0000000..25642a7 --- /dev/null +++ b/ml-data science tutorials/logs.log @@ -0,0 +1,7857 @@ +2023-11-09 09:57:32,418:WARNING: +'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. +2023-11-09 09:57:32,418:WARNING: +'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. +2023-11-09 09:57:32,418:WARNING: +'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. +2023-11-09 09:57:32,418:WARNING: +'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. +2023-11-09 09:57:55,172:INFO:PyCaret RegressionExperiment +2023-11-09 09:57:55,172:INFO:Logging name: reg-default-name +2023-11-09 09:57:55,172:INFO:ML Usecase: MLUsecase.REGRESSION +2023-11-09 09:57:55,172:INFO:version 3.1.0 +2023-11-09 09:57:55,173:INFO:Initializing setup() +2023-11-09 09:57:55,173:INFO:self.USI: 9d6e +2023-11-09 09:57:55,173:INFO:self._variable_keys: {'fold_generator', 'pipeline', 'fold_groups_param', 'n_jobs_param', 'memory', 'idx', 'log_plots_param', 'transform_target_param', 'USI', 'y_train', 'X', 'exp_id', 'gpu_param', 'y_test', 'target_param', 'X_train', 'exp_name_log', 'y', 'X_test', 'html_param', '_ml_usecase', 'seed', 'gpu_n_jobs_param', 'data', '_available_plots', 'fold_shuffle_param', 'logging_param'} +2023-11-09 09:57:55,173:INFO:Checking environment +2023-11-09 09:57:55,173:INFO:python_version: 3.8.18 +2023-11-09 09:57:55,173:INFO:python_build: ('default', 'Sep 11 2023 13:40:15') +2023-11-09 09:57:55,173:INFO:machine: x86_64 +2023-11-09 09:57:55,173:INFO:platform: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 09:57:55,173:INFO:Memory: svmem(total=8315187200, available=4932845568, percent=40.7, used=3047759872, free=196444160, active=1336061952, inactive=5946228736, buffers=317767680, cached=4753215488, shared=4423680, slab=647933952) +2023-11-09 09:57:55,174:INFO:Physical Core: 1 +2023-11-09 09:57:55,174:INFO:Logical Core: 2 +2023-11-09 09:57:55,174:INFO:Checking libraries +2023-11-09 09:57:55,174:INFO:System: +2023-11-09 09:57:55,174:INFO: python: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] +2023-11-09 09:57:55,174:INFO:executable: /workspaces/D2I-Jupyter-Notebook-Tools/.conda/bin/python +2023-11-09 09:57:55,174:INFO: machine: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 09:57:55,174:INFO:PyCaret required dependencies: +2023-11-09 09:57:55,239:INFO: pip: 23.3 +2023-11-09 09:57:55,239:INFO: setuptools: 68.0.0 +2023-11-09 09:57:55,239:INFO: pycaret: 3.1.0 +2023-11-09 09:57:55,239:INFO: IPython: 8.12.0 +2023-11-09 09:57:55,240:INFO: ipywidgets: 8.1.1 +2023-11-09 09:57:55,240:INFO: tqdm: 4.66.1 +2023-11-09 09:57:55,240:INFO: numpy: 1.23.5 +2023-11-09 09:57:55,240:INFO: pandas: 1.5.3 +2023-11-09 09:57:55,240:INFO: jinja2: 3.1.2 +2023-11-09 09:57:55,241:INFO: scipy: 1.10.1 +2023-11-09 09:57:55,241:INFO: joblib: 1.3.2 +2023-11-09 09:57:55,241:INFO: sklearn: 1.2.2 +2023-11-09 09:57:55,241:INFO: pyod: 1.1.1 +2023-11-09 09:57:55,241:INFO: imblearn: 0.11.0 +2023-11-09 09:57:55,241:INFO: category_encoders: 2.6.3 +2023-11-09 09:57:55,241:INFO: lightgbm: 4.1.0 +2023-11-09 09:57:55,241:INFO: numba: 0.58.1 +2023-11-09 09:57:55,241:INFO: requests: 2.31.0 +2023-11-09 09:57:55,241:INFO: matplotlib: 3.7.3 +2023-11-09 09:57:55,241:INFO: scikitplot: 0.3.7 +2023-11-09 09:57:55,242:INFO: yellowbrick: 1.5 +2023-11-09 09:57:55,242:INFO: plotly: 5.18.0 +2023-11-09 09:57:55,242:INFO: plotly-resampler: Not installed +2023-11-09 09:57:55,242:INFO: kaleido: 0.2.1 +2023-11-09 09:57:55,242:INFO: schemdraw: 0.15 +2023-11-09 09:57:55,242:INFO: statsmodels: 0.14.0 +2023-11-09 09:57:55,242:INFO: sktime: 0.21.1 +2023-11-09 09:57:55,242:INFO: tbats: 1.1.3 +2023-11-09 09:57:55,242:INFO: pmdarima: 2.0.4 +2023-11-09 09:57:55,242:INFO: psutil: 5.9.0 +2023-11-09 09:57:55,242:INFO: markupsafe: 2.1.3 +2023-11-09 09:57:55,242:INFO: pickle5: Not installed +2023-11-09 09:57:55,242:INFO: cloudpickle: 3.0.0 +2023-11-09 09:57:55,242:INFO: deprecation: 2.1.0 +2023-11-09 09:57:55,242:INFO: xxhash: 3.4.1 +2023-11-09 09:57:55,242:INFO: wurlitzer: 3.0.3 +2023-11-09 09:57:55,242:INFO:PyCaret optional dependencies: +2023-11-09 09:57:55,261:INFO: shap: Not installed +2023-11-09 09:57:55,261:INFO: interpret: Not installed +2023-11-09 09:57:55,261:INFO: umap: Not installed +2023-11-09 09:57:55,261:INFO: ydata_profiling: Not installed +2023-11-09 09:57:55,261:INFO: explainerdashboard: Not installed +2023-11-09 09:57:55,261:INFO: autoviz: Not installed +2023-11-09 09:57:55,261:INFO: fairlearn: Not installed +2023-11-09 09:57:55,261:INFO: deepchecks: Not installed +2023-11-09 09:57:55,261:INFO: xgboost: Not installed +2023-11-09 09:57:55,262:INFO: catboost: Not installed +2023-11-09 09:57:55,262:INFO: kmodes: Not installed +2023-11-09 09:57:55,262:INFO: mlxtend: Not installed +2023-11-09 09:57:55,262:INFO: statsforecast: Not installed +2023-11-09 09:57:55,262:INFO: tune_sklearn: Not installed +2023-11-09 09:57:55,262:INFO: ray: Not installed +2023-11-09 09:57:55,262:INFO: hyperopt: Not installed +2023-11-09 09:57:55,262:INFO: optuna: Not installed +2023-11-09 09:57:55,262:INFO: skopt: Not installed +2023-11-09 09:57:55,262:INFO: mlflow: Not installed +2023-11-09 09:57:55,262:INFO: gradio: Not installed +2023-11-09 09:57:55,262:INFO: fastapi: Not installed +2023-11-09 09:57:55,262:INFO: uvicorn: Not installed +2023-11-09 09:57:55,262:INFO: m2cgen: Not installed +2023-11-09 09:57:55,262:INFO: evidently: Not installed +2023-11-09 09:57:55,262:INFO: fugue: Not installed +2023-11-09 09:57:55,262:INFO: streamlit: Not installed +2023-11-09 09:57:55,263:INFO: prophet: Not installed +2023-11-09 09:57:55,263:INFO:None +2023-11-09 09:57:55,263:INFO:Set up data. +2023-11-09 09:58:51,037:INFO:PyCaret RegressionExperiment +2023-11-09 09:58:51,037:INFO:Logging name: reg-default-name +2023-11-09 09:58:51,037:INFO:ML Usecase: MLUsecase.REGRESSION +2023-11-09 09:58:51,037:INFO:version 3.1.0 +2023-11-09 09:58:51,037:INFO:Initializing setup() +2023-11-09 09:58:51,037:INFO:self.USI: 2184 +2023-11-09 09:58:51,037:INFO:self._variable_keys: {'fold_generator', 'pipeline', 'fold_groups_param', 'n_jobs_param', 'memory', 'idx', 'log_plots_param', 'transform_target_param', 'USI', 'y_train', 'X', 'exp_id', 'gpu_param', 'y_test', 'target_param', 'X_train', 'exp_name_log', 'y', 'X_test', 'html_param', '_ml_usecase', 'seed', 'gpu_n_jobs_param', 'data', '_available_plots', 'fold_shuffle_param', 'logging_param'} +2023-11-09 09:58:51,037:INFO:Checking environment +2023-11-09 09:58:51,037:INFO:python_version: 3.8.18 +2023-11-09 09:58:51,037:INFO:python_build: ('default', 'Sep 11 2023 13:40:15') +2023-11-09 09:58:51,037:INFO:machine: x86_64 +2023-11-09 09:58:51,038:INFO:platform: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 09:58:51,038:INFO:Memory: svmem(total=8315187200, available=4912762880, percent=40.9, used=3067842560, free=191614976, active=1342439424, inactive=5921595392, buffers=320319488, cached=4735410176, shared=4423680, slab=647843840) +2023-11-09 09:58:51,038:INFO:Physical Core: 1 +2023-11-09 09:58:51,038:INFO:Logical Core: 2 +2023-11-09 09:58:51,038:INFO:Checking libraries +2023-11-09 09:58:51,038:INFO:System: +2023-11-09 09:58:51,038:INFO: python: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] +2023-11-09 09:58:51,038:INFO:executable: /workspaces/D2I-Jupyter-Notebook-Tools/.conda/bin/python +2023-11-09 09:58:51,038:INFO: machine: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 09:58:51,039:INFO:PyCaret required dependencies: +2023-11-09 09:58:51,039:INFO: pip: 23.3 +2023-11-09 09:58:51,039:INFO: setuptools: 68.0.0 +2023-11-09 09:58:51,039:INFO: pycaret: 3.1.0 +2023-11-09 09:58:51,039:INFO: IPython: 8.12.0 +2023-11-09 09:58:51,039:INFO: ipywidgets: 8.1.1 +2023-11-09 09:58:51,039:INFO: tqdm: 4.66.1 +2023-11-09 09:58:51,039:INFO: numpy: 1.23.5 +2023-11-09 09:58:51,039:INFO: pandas: 1.5.3 +2023-11-09 09:58:51,039:INFO: jinja2: 3.1.2 +2023-11-09 09:58:51,039:INFO: scipy: 1.10.1 +2023-11-09 09:58:51,039:INFO: joblib: 1.3.2 +2023-11-09 09:58:51,039:INFO: sklearn: 1.2.2 +2023-11-09 09:58:51,039:INFO: pyod: 1.1.1 +2023-11-09 09:58:51,039:INFO: imblearn: 0.11.0 +2023-11-09 09:58:51,039:INFO: category_encoders: 2.6.3 +2023-11-09 09:58:51,039:INFO: lightgbm: 4.1.0 +2023-11-09 09:58:51,039:INFO: numba: 0.58.1 +2023-11-09 09:58:51,040:INFO: requests: 2.31.0 +2023-11-09 09:58:51,040:INFO: matplotlib: 3.7.3 +2023-11-09 09:58:51,040:INFO: scikitplot: 0.3.7 +2023-11-09 09:58:51,040:INFO: yellowbrick: 1.5 +2023-11-09 09:58:51,040:INFO: plotly: 5.18.0 +2023-11-09 09:58:51,040:INFO: plotly-resampler: Not installed +2023-11-09 09:58:51,040:INFO: kaleido: 0.2.1 +2023-11-09 09:58:51,040:INFO: schemdraw: 0.15 +2023-11-09 09:58:51,040:INFO: statsmodels: 0.14.0 +2023-11-09 09:58:51,040:INFO: sktime: 0.21.1 +2023-11-09 09:58:51,040:INFO: tbats: 1.1.3 +2023-11-09 09:58:51,040:INFO: pmdarima: 2.0.4 +2023-11-09 09:58:51,040:INFO: psutil: 5.9.0 +2023-11-09 09:58:51,040:INFO: markupsafe: 2.1.3 +2023-11-09 09:58:51,040:INFO: pickle5: Not installed +2023-11-09 09:58:51,040:INFO: cloudpickle: 3.0.0 +2023-11-09 09:58:51,040:INFO: deprecation: 2.1.0 +2023-11-09 09:58:51,040:INFO: xxhash: 3.4.1 +2023-11-09 09:58:51,040:INFO: wurlitzer: 3.0.3 +2023-11-09 09:58:51,040:INFO:PyCaret optional dependencies: +2023-11-09 09:58:51,041:INFO: shap: Not installed +2023-11-09 09:58:51,041:INFO: interpret: Not installed +2023-11-09 09:58:51,041:INFO: umap: Not installed +2023-11-09 09:58:51,041:INFO: ydata_profiling: Not installed +2023-11-09 09:58:51,041:INFO: explainerdashboard: Not installed +2023-11-09 09:58:51,041:INFO: autoviz: Not installed +2023-11-09 09:58:51,041:INFO: fairlearn: Not installed +2023-11-09 09:58:51,041:INFO: deepchecks: Not installed +2023-11-09 09:58:51,041:INFO: xgboost: Not installed +2023-11-09 09:58:51,041:INFO: catboost: Not installed +2023-11-09 09:58:51,041:INFO: kmodes: Not installed +2023-11-09 09:58:51,041:INFO: mlxtend: Not installed +2023-11-09 09:58:51,041:INFO: statsforecast: Not installed +2023-11-09 09:58:51,041:INFO: tune_sklearn: Not installed +2023-11-09 09:58:51,041:INFO: ray: Not installed +2023-11-09 09:58:51,041:INFO: hyperopt: Not installed +2023-11-09 09:58:51,041:INFO: optuna: Not installed +2023-11-09 09:58:51,041:INFO: skopt: Not installed +2023-11-09 09:58:51,041:INFO: mlflow: Not installed +2023-11-09 09:58:51,042:INFO: gradio: Not installed +2023-11-09 09:58:51,042:INFO: fastapi: Not installed +2023-11-09 09:58:51,042:INFO: uvicorn: Not installed +2023-11-09 09:58:51,042:INFO: m2cgen: Not installed +2023-11-09 09:58:51,042:INFO: evidently: Not installed +2023-11-09 09:58:51,042:INFO: fugue: Not installed +2023-11-09 09:58:51,042:INFO: streamlit: Not installed +2023-11-09 09:58:51,042:INFO: prophet: Not installed +2023-11-09 09:58:51,042:INFO:None +2023-11-09 09:58:51,042:INFO:Set up data. +2023-11-09 09:58:51,047:INFO:Set up folding strategy. +2023-11-09 10:01:36,096:INFO:PyCaret RegressionExperiment +2023-11-09 10:01:36,096:INFO:Logging name: reg-default-name +2023-11-09 10:01:36,096:INFO:ML Usecase: MLUsecase.REGRESSION +2023-11-09 10:01:36,097:INFO:version 3.1.0 +2023-11-09 10:01:36,097:INFO:Initializing setup() +2023-11-09 10:01:36,097:INFO:self.USI: 095c +2023-11-09 10:01:36,097:INFO:self._variable_keys: {'fold_generator', 'pipeline', 'fold_groups_param', 'n_jobs_param', 'memory', 'idx', 'log_plots_param', 'transform_target_param', 'USI', 'y_train', 'X', 'exp_id', 'gpu_param', 'y_test', 'target_param', 'X_train', 'exp_name_log', 'y', 'X_test', 'html_param', '_ml_usecase', 'seed', 'gpu_n_jobs_param', 'data', '_available_plots', 'fold_shuffle_param', 'logging_param'} +2023-11-09 10:01:36,097:INFO:Checking environment +2023-11-09 10:01:36,097:INFO:python_version: 3.8.18 +2023-11-09 10:01:36,097:INFO:python_build: ('default', 'Sep 11 2023 13:40:15') +2023-11-09 10:01:36,097:INFO:machine: x86_64 +2023-11-09 10:01:36,097:INFO:platform: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 10:01:36,097:INFO:Memory: svmem(total=8315187200, available=5006782464, percent=39.8, used=2973822976, free=281190400, active=1343188992, inactive=5892014080, buffers=321576960, cached=4738596864, shared=4423680, slab=647929856) +2023-11-09 10:01:36,098:INFO:Physical Core: 1 +2023-11-09 10:01:36,098:INFO:Logical Core: 2 +2023-11-09 10:01:36,099:INFO:Checking libraries +2023-11-09 10:01:36,099:INFO:System: +2023-11-09 10:01:36,099:INFO: python: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] +2023-11-09 10:01:36,099:INFO:executable: /workspaces/D2I-Jupyter-Notebook-Tools/.conda/bin/python +2023-11-09 10:01:36,099:INFO: machine: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 10:01:36,099:INFO:PyCaret required dependencies: +2023-11-09 10:01:36,099:INFO: pip: 23.3 +2023-11-09 10:01:36,099:INFO: setuptools: 68.0.0 +2023-11-09 10:01:36,100:INFO: pycaret: 3.1.0 +2023-11-09 10:01:36,100:INFO: IPython: 8.12.0 +2023-11-09 10:01:36,100:INFO: ipywidgets: 8.1.1 +2023-11-09 10:01:36,100:INFO: tqdm: 4.66.1 +2023-11-09 10:01:36,100:INFO: numpy: 1.23.5 +2023-11-09 10:01:36,100:INFO: pandas: 1.5.3 +2023-11-09 10:01:36,100:INFO: jinja2: 3.1.2 +2023-11-09 10:01:36,100:INFO: scipy: 1.10.1 +2023-11-09 10:01:36,101:INFO: joblib: 1.3.2 +2023-11-09 10:01:36,101:INFO: sklearn: 1.2.2 +2023-11-09 10:01:36,101:INFO: pyod: 1.1.1 +2023-11-09 10:01:36,101:INFO: imblearn: 0.11.0 +2023-11-09 10:01:36,101:INFO: category_encoders: 2.6.3 +2023-11-09 10:01:36,101:INFO: lightgbm: 4.1.0 +2023-11-09 10:01:36,101:INFO: numba: 0.58.1 +2023-11-09 10:01:36,102:INFO: requests: 2.31.0 +2023-11-09 10:01:36,102:INFO: matplotlib: 3.7.3 +2023-11-09 10:01:36,102:INFO: scikitplot: 0.3.7 +2023-11-09 10:01:36,102:INFO: yellowbrick: 1.5 +2023-11-09 10:01:36,102:INFO: plotly: 5.18.0 +2023-11-09 10:01:36,102:INFO: plotly-resampler: Not installed +2023-11-09 10:01:36,102:INFO: kaleido: 0.2.1 +2023-11-09 10:01:36,102:INFO: schemdraw: 0.15 +2023-11-09 10:01:36,102:INFO: statsmodels: 0.14.0 +2023-11-09 10:01:36,102:INFO: sktime: 0.21.1 +2023-11-09 10:01:36,102:INFO: tbats: 1.1.3 +2023-11-09 10:01:36,102:INFO: pmdarima: 2.0.4 +2023-11-09 10:01:36,102:INFO: psutil: 5.9.0 +2023-11-09 10:01:36,102:INFO: markupsafe: 2.1.3 +2023-11-09 10:01:36,102:INFO: pickle5: Not installed +2023-11-09 10:01:36,102:INFO: cloudpickle: 3.0.0 +2023-11-09 10:01:36,102:INFO: deprecation: 2.1.0 +2023-11-09 10:01:36,102:INFO: xxhash: 3.4.1 +2023-11-09 10:01:36,103:INFO: wurlitzer: 3.0.3 +2023-11-09 10:01:36,103:INFO:PyCaret optional dependencies: +2023-11-09 10:01:36,103:INFO: shap: Not installed +2023-11-09 10:01:36,103:INFO: interpret: Not installed +2023-11-09 10:01:36,103:INFO: umap: Not installed +2023-11-09 10:01:36,103:INFO: ydata_profiling: Not installed +2023-11-09 10:01:36,103:INFO: explainerdashboard: Not installed +2023-11-09 10:01:36,103:INFO: autoviz: Not installed +2023-11-09 10:01:36,103:INFO: fairlearn: Not installed +2023-11-09 10:01:36,103:INFO: deepchecks: Not installed +2023-11-09 10:01:36,103:INFO: xgboost: Not installed +2023-11-09 10:01:36,103:INFO: catboost: Not installed +2023-11-09 10:01:36,103:INFO: kmodes: Not installed +2023-11-09 10:01:36,103:INFO: mlxtend: Not installed +2023-11-09 10:01:36,103:INFO: statsforecast: Not installed +2023-11-09 10:01:36,103:INFO: tune_sklearn: Not installed +2023-11-09 10:01:36,103:INFO: ray: Not installed +2023-11-09 10:01:36,104:INFO: hyperopt: Not installed +2023-11-09 10:01:36,104:INFO: optuna: Not installed +2023-11-09 10:01:36,104:INFO: skopt: Not installed +2023-11-09 10:01:36,104:INFO: mlflow: Not installed +2023-11-09 10:01:36,104:INFO: gradio: Not installed +2023-11-09 10:01:36,104:INFO: fastapi: Not installed +2023-11-09 10:01:36,104:INFO: uvicorn: Not installed +2023-11-09 10:01:36,104:INFO: m2cgen: Not installed +2023-11-09 10:01:36,104:INFO: evidently: Not installed +2023-11-09 10:01:36,104:INFO: fugue: Not installed +2023-11-09 10:01:36,104:INFO: streamlit: Not installed +2023-11-09 10:01:36,104:INFO: prophet: Not installed +2023-11-09 10:01:36,104:INFO:None +2023-11-09 10:01:36,104:INFO:Set up data. +2023-11-09 10:01:36,109:INFO:Set up folding strategy. +2023-11-09 10:01:36,109:INFO:Set up train/test split. +2023-11-09 10:01:36,109:INFO:Set up data. +2023-11-09 10:01:36,112:INFO:Set up index. +2023-11-09 10:01:36,113:INFO:Assigning column types. +2023-11-09 10:01:36,115:INFO:Engine successfully changes for model 'lr' to 'sklearn'. +2023-11-09 10:01:36,115:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,119:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,123:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,173:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,211:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,212:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,212:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,213:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,216:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,221:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,277:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,315:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,316:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,316:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,316:INFO:Engine successfully changes for model 'lasso' to 'sklearn'. +2023-11-09 10:01:36,321:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,325:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,379:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,418:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,418:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,418:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,422:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,426:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,475:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,514:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,514:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,515:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,515:INFO:Engine successfully changes for model 'ridge' to 'sklearn'. +2023-11-09 10:01:36,522:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,570:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,608:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,608:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,609:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,617:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,664:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,701:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,702:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,702:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,702:INFO:Engine successfully changes for model 'en' to 'sklearn'. +2023-11-09 10:01:36,759:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,796:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,796:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,796:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,854:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,895:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,895:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,895:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,896:INFO:Engine successfully changes for model 'knn' to 'sklearn'. +2023-11-09 10:01:36,952:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:01:36,992:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:36,992:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:37,056:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:01:37,094:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:37,094:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:37,094:INFO:Engine successfully changes for model 'svm' to 'sklearn'. +2023-11-09 10:01:37,191:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:37,191:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:37,405:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:37,406:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:37,407:INFO:Preparing preprocessing pipeline... +2023-11-09 10:01:37,407:INFO:Set up target transformation. +2023-11-09 10:01:37,408:INFO:Set up simple imputation. +2023-11-09 10:01:37,409:INFO:Set up column name cleaning. +2023-11-09 10:01:37,439:INFO:Finished creating preprocessing pipeline. +2023-11-09 10:01:37,445:INFO:Pipeline: Pipeline(memory=FastMemory(location=/tmp/joblib), + steps=[('target_transformation', + TransformerWrapperWithInverse(transformer=TargetTransformer(estimator=PowerTransformer(standardize=False)))), + ('numerical_imputer', + TransformerWrapper(include=['Year', 'Series'], + transformer=SimpleImputer())), + ('categorical_imputer', + TransformerWrapper(include=[], + transformer=SimpleImputer(strategy='most_frequent'))), + ('clean_column_names', + TransformerWrapper(transformer=CleanColumnNames()))]) +2023-11-09 10:01:37,445:INFO:Creating final display dataframe. +2023-11-09 10:01:37,516:INFO:Setup _display_container: Description Value +0 Session id 123 +1 Target Average price All property types +2 Target type Regression +3 Original data shape (523, 4) +4 Transformed data shape (523, 4) +5 Transformed train set shape (372, 4) +6 Transformed test set shape (151, 4) +7 Numeric features 2 +8 Preprocess True +9 Imputation type simple +10 Numeric imputation mean +11 Categorical imputation mode +12 Transform target True +13 Transform target method yeo-johnson +14 Fold Generator TimeSeriesSplit +15 Fold Number 3 +16 CPU Jobs -1 +17 Use GPU False +18 Log Experiment False +19 Experiment Name reg-default-name +20 USI 095c +2023-11-09 10:01:37,625:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:37,626:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:37,729:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:37,730:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:01:37,730:INFO:setup() successfully completed in 1.63s............... +2023-11-09 10:01:54,954:INFO:Initializing compare_models() +2023-11-09 10:01:54,955:INFO:compare_models(self=, include=None, fold=None, round=4, cross_validation=True, sort=MAE, n_select=1, budget_time=None, turbo=True, errors=ignore, fit_kwargs=None, groups=None, experiment_custom_tags=None, probability_threshold=None, verbose=True, parallel=None, caller_params={'self': , 'include': None, 'exclude': None, 'fold': None, 'round': 4, 'cross_validation': True, 'sort': 'MAE', 'n_select': 1, 'budget_time': None, 'turbo': True, 'errors': 'ignore', 'fit_kwargs': None, 'groups': None, 'experiment_custom_tags': None, 'engine': None, 'verbose': True, 'parallel': None, '__class__': }, exclude=None) +2023-11-09 10:01:54,955:INFO:Checking exceptions +2023-11-09 10:01:54,957:INFO:Preparing display monitor +2023-11-09 10:01:54,981:INFO:Initializing Linear Regression +2023-11-09 10:01:54,981:INFO:Total runtime is 4.1961669921875e-06 minutes +2023-11-09 10:01:54,984:INFO:SubProcess create_model() called ================================== +2023-11-09 10:01:54,984:INFO:Initializing create_model() +2023-11-09 10:01:54,984:INFO:create_model(self=, estimator=lr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:01:54,985:INFO:Checking exceptions +2023-11-09 10:01:54,985:INFO:Importing libraries +2023-11-09 10:01:54,985:INFO:Copying training dataset +2023-11-09 10:01:54,988:INFO:Defining folds +2023-11-09 10:01:54,988:INFO:Declaring metric variables +2023-11-09 10:01:54,991:INFO:Importing untrained model +2023-11-09 10:01:54,994:INFO:Linear Regression Imported successfully +2023-11-09 10:01:54,999:INFO:Starting cross validation +2023-11-09 10:01:55,002:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:01:57,255:INFO:Calculating mean and std +2023-11-09 10:01:57,257:INFO:Creating metrics dataframe +2023-11-09 10:01:57,262:INFO:Uploading results into container +2023-11-09 10:01:57,263:INFO:Uploading model into container now +2023-11-09 10:01:57,281:INFO:_master_model_container: 1 +2023-11-09 10:01:57,281:INFO:_display_container: 2 +2023-11-09 10:01:57,281:INFO:LinearRegression(n_jobs=-1) +2023-11-09 10:01:57,281:INFO:create_model() successfully completed...................................... +2023-11-09 10:01:57,378:INFO:SubProcess create_model() end ================================== +2023-11-09 10:01:57,378:INFO:Creating metrics dataframe +2023-11-09 10:01:57,386:INFO:Initializing Lasso Regression +2023-11-09 10:01:57,386:INFO:Total runtime is 0.04008920192718506 minutes +2023-11-09 10:01:57,389:INFO:SubProcess create_model() called ================================== +2023-11-09 10:01:57,390:INFO:Initializing create_model() +2023-11-09 10:01:57,390:INFO:create_model(self=, estimator=lasso, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:01:57,390:INFO:Checking exceptions +2023-11-09 10:01:57,390:INFO:Importing libraries +2023-11-09 10:01:57,391:INFO:Copying training dataset +2023-11-09 10:01:57,394:INFO:Defining folds +2023-11-09 10:01:57,394:INFO:Declaring metric variables +2023-11-09 10:01:57,397:INFO:Importing untrained model +2023-11-09 10:01:57,401:INFO:Lasso Regression Imported successfully +2023-11-09 10:01:57,407:INFO:Starting cross validation +2023-11-09 10:01:57,408:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:01:57,480:INFO:Calculating mean and std +2023-11-09 10:01:57,481:INFO:Creating metrics dataframe +2023-11-09 10:01:57,484:INFO:Uploading results into container +2023-11-09 10:01:57,484:INFO:Uploading model into container now +2023-11-09 10:01:57,484:INFO:_master_model_container: 2 +2023-11-09 10:01:57,485:INFO:_display_container: 2 +2023-11-09 10:01:57,485:INFO:Lasso(random_state=123) +2023-11-09 10:01:57,485:INFO:create_model() successfully completed...................................... +2023-11-09 10:01:57,576:INFO:SubProcess create_model() end ================================== +2023-11-09 10:01:57,576:INFO:Creating metrics dataframe +2023-11-09 10:01:57,588:INFO:Initializing Ridge Regression +2023-11-09 10:01:57,588:INFO:Total runtime is 0.04345134099324545 minutes +2023-11-09 10:01:57,592:INFO:SubProcess create_model() called ================================== +2023-11-09 10:01:57,592:INFO:Initializing create_model() +2023-11-09 10:01:57,592:INFO:create_model(self=, estimator=ridge, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:01:57,592:INFO:Checking exceptions +2023-11-09 10:01:57,592:INFO:Importing libraries +2023-11-09 10:01:57,592:INFO:Copying training dataset +2023-11-09 10:01:57,597:INFO:Defining folds +2023-11-09 10:01:57,598:INFO:Declaring metric variables +2023-11-09 10:01:57,601:INFO:Importing untrained model +2023-11-09 10:01:57,605:INFO:Ridge Regression Imported successfully +2023-11-09 10:01:57,612:INFO:Starting cross validation +2023-11-09 10:01:57,613:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:01:57,721:INFO:Calculating mean and std +2023-11-09 10:01:57,723:INFO:Creating metrics dataframe +2023-11-09 10:01:57,728:INFO:Uploading results into container +2023-11-09 10:01:57,728:INFO:Uploading model into container now +2023-11-09 10:01:57,729:INFO:_master_model_container: 3 +2023-11-09 10:01:57,729:INFO:_display_container: 2 +2023-11-09 10:01:57,729:INFO:Ridge(random_state=123) +2023-11-09 10:01:57,729:INFO:create_model() successfully completed...................................... +2023-11-09 10:01:57,866:INFO:SubProcess create_model() end ================================== +2023-11-09 10:01:57,867:INFO:Creating metrics dataframe +2023-11-09 10:01:57,879:INFO:Initializing Elastic Net +2023-11-09 10:01:57,879:INFO:Total runtime is 0.048310124874115 minutes +2023-11-09 10:01:57,884:INFO:SubProcess create_model() called ================================== +2023-11-09 10:01:57,884:INFO:Initializing create_model() +2023-11-09 10:01:57,884:INFO:create_model(self=, estimator=en, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:01:57,884:INFO:Checking exceptions +2023-11-09 10:01:57,884:INFO:Importing libraries +2023-11-09 10:01:57,884:INFO:Copying training dataset +2023-11-09 10:01:57,891:INFO:Defining folds +2023-11-09 10:01:57,891:INFO:Declaring metric variables +2023-11-09 10:01:57,896:INFO:Importing untrained model +2023-11-09 10:01:57,899:INFO:Elastic Net Imported successfully +2023-11-09 10:01:57,905:INFO:Starting cross validation +2023-11-09 10:01:57,907:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:01:57,976:INFO:Calculating mean and std +2023-11-09 10:01:57,976:INFO:Creating metrics dataframe +2023-11-09 10:01:57,979:INFO:Uploading results into container +2023-11-09 10:01:57,979:INFO:Uploading model into container now +2023-11-09 10:01:57,980:INFO:_master_model_container: 4 +2023-11-09 10:01:57,980:INFO:_display_container: 2 +2023-11-09 10:01:57,980:INFO:ElasticNet(random_state=123) +2023-11-09 10:01:57,980:INFO:create_model() successfully completed...................................... +2023-11-09 10:01:58,060:INFO:SubProcess create_model() end ================================== +2023-11-09 10:01:58,060:INFO:Creating metrics dataframe +2023-11-09 10:01:58,068:INFO:Initializing Least Angle Regression +2023-11-09 10:01:58,069:INFO:Total runtime is 0.05146764516830445 minutes +2023-11-09 10:01:58,072:INFO:SubProcess create_model() called ================================== +2023-11-09 10:01:58,072:INFO:Initializing create_model() +2023-11-09 10:01:58,072:INFO:create_model(self=, estimator=lar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:01:58,072:INFO:Checking exceptions +2023-11-09 10:01:58,073:INFO:Importing libraries +2023-11-09 10:01:58,073:INFO:Copying training dataset +2023-11-09 10:01:58,076:INFO:Defining folds +2023-11-09 10:01:58,077:INFO:Declaring metric variables +2023-11-09 10:01:58,080:INFO:Importing untrained model +2023-11-09 10:01:58,083:INFO:Least Angle Regression Imported successfully +2023-11-09 10:01:58,088:INFO:Starting cross validation +2023-11-09 10:01:58,090:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:01:58,157:INFO:Calculating mean and std +2023-11-09 10:01:58,158:INFO:Creating metrics dataframe +2023-11-09 10:01:58,160:INFO:Uploading results into container +2023-11-09 10:01:58,161:INFO:Uploading model into container now +2023-11-09 10:01:58,161:INFO:_master_model_container: 5 +2023-11-09 10:01:58,161:INFO:_display_container: 2 +2023-11-09 10:01:58,161:INFO:Lars(random_state=123) +2023-11-09 10:01:58,162:INFO:create_model() successfully completed...................................... +2023-11-09 10:01:58,260:INFO:SubProcess create_model() end ================================== +2023-11-09 10:01:58,260:INFO:Creating metrics dataframe +2023-11-09 10:01:58,272:INFO:Initializing Lasso Least Angle Regression +2023-11-09 10:01:58,272:INFO:Total runtime is 0.054855755964914966 minutes +2023-11-09 10:01:58,275:INFO:SubProcess create_model() called ================================== +2023-11-09 10:01:58,276:INFO:Initializing create_model() +2023-11-09 10:01:58,276:INFO:create_model(self=, estimator=llar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:01:58,276:INFO:Checking exceptions +2023-11-09 10:01:58,276:INFO:Importing libraries +2023-11-09 10:01:58,276:INFO:Copying training dataset +2023-11-09 10:01:58,280:INFO:Defining folds +2023-11-09 10:01:58,280:INFO:Declaring metric variables +2023-11-09 10:01:58,284:INFO:Importing untrained model +2023-11-09 10:01:58,288:INFO:Lasso Least Angle Regression Imported successfully +2023-11-09 10:01:58,296:INFO:Starting cross validation +2023-11-09 10:01:58,297:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:01:58,383:INFO:Calculating mean and std +2023-11-09 10:01:58,384:INFO:Creating metrics dataframe +2023-11-09 10:01:58,389:INFO:Uploading results into container +2023-11-09 10:01:58,389:INFO:Uploading model into container now +2023-11-09 10:01:58,390:INFO:_master_model_container: 6 +2023-11-09 10:01:58,390:INFO:_display_container: 2 +2023-11-09 10:01:58,390:INFO:LassoLars(random_state=123) +2023-11-09 10:01:58,390:INFO:create_model() successfully completed...................................... +2023-11-09 10:01:58,480:INFO:SubProcess create_model() end ================================== +2023-11-09 10:01:58,480:INFO:Creating metrics dataframe +2023-11-09 10:01:58,493:INFO:Initializing Orthogonal Matching Pursuit +2023-11-09 10:01:58,493:INFO:Total runtime is 0.05854492187500001 minutes +2023-11-09 10:01:58,497:INFO:SubProcess create_model() called ================================== +2023-11-09 10:01:58,497:INFO:Initializing create_model() +2023-11-09 10:01:58,498:INFO:create_model(self=, estimator=omp, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:01:58,498:INFO:Checking exceptions +2023-11-09 10:01:58,498:INFO:Importing libraries +2023-11-09 10:01:58,498:INFO:Copying training dataset +2023-11-09 10:01:58,502:INFO:Defining folds +2023-11-09 10:01:58,502:INFO:Declaring metric variables +2023-11-09 10:01:58,508:INFO:Importing untrained model +2023-11-09 10:01:58,512:INFO:Orthogonal Matching Pursuit Imported successfully +2023-11-09 10:01:58,520:INFO:Starting cross validation +2023-11-09 10:01:58,521:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:01:58,619:INFO:Calculating mean and std +2023-11-09 10:01:58,620:INFO:Creating metrics dataframe +2023-11-09 10:01:58,626:INFO:Uploading results into container +2023-11-09 10:01:58,626:INFO:Uploading model into container now +2023-11-09 10:01:58,627:INFO:_master_model_container: 7 +2023-11-09 10:01:58,627:INFO:_display_container: 2 +2023-11-09 10:01:58,627:INFO:OrthogonalMatchingPursuit() +2023-11-09 10:01:58,627:INFO:create_model() successfully completed...................................... +2023-11-09 10:01:58,726:INFO:SubProcess create_model() end ================================== +2023-11-09 10:01:58,726:INFO:Creating metrics dataframe +2023-11-09 10:01:58,738:INFO:Initializing Bayesian Ridge +2023-11-09 10:01:58,738:INFO:Total runtime is 0.06262396574020387 minutes +2023-11-09 10:01:58,742:INFO:SubProcess create_model() called ================================== +2023-11-09 10:01:58,742:INFO:Initializing create_model() +2023-11-09 10:01:58,742:INFO:create_model(self=, estimator=br, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:01:58,742:INFO:Checking exceptions +2023-11-09 10:01:58,743:INFO:Importing libraries +2023-11-09 10:01:58,743:INFO:Copying training dataset +2023-11-09 10:01:58,748:INFO:Defining folds +2023-11-09 10:01:58,748:INFO:Declaring metric variables +2023-11-09 10:01:58,752:INFO:Importing untrained model +2023-11-09 10:01:58,756:INFO:Bayesian Ridge Imported successfully +2023-11-09 10:01:58,764:INFO:Starting cross validation +2023-11-09 10:01:58,765:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:01:58,837:INFO:Calculating mean and std +2023-11-09 10:01:58,838:INFO:Creating metrics dataframe +2023-11-09 10:01:58,840:INFO:Uploading results into container +2023-11-09 10:01:58,841:INFO:Uploading model into container now +2023-11-09 10:01:58,841:INFO:_master_model_container: 8 +2023-11-09 10:01:58,841:INFO:_display_container: 2 +2023-11-09 10:01:58,841:INFO:BayesianRidge() +2023-11-09 10:01:58,842:INFO:create_model() successfully completed...................................... +2023-11-09 10:01:58,921:INFO:SubProcess create_model() end ================================== +2023-11-09 10:01:58,921:INFO:Creating metrics dataframe +2023-11-09 10:01:58,930:INFO:Initializing Passive Aggressive Regressor +2023-11-09 10:01:58,930:INFO:Total runtime is 0.06582495768864952 minutes +2023-11-09 10:01:58,933:INFO:SubProcess create_model() called ================================== +2023-11-09 10:01:58,934:INFO:Initializing create_model() +2023-11-09 10:01:58,934:INFO:create_model(self=, estimator=par, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:01:58,934:INFO:Checking exceptions +2023-11-09 10:01:58,934:INFO:Importing libraries +2023-11-09 10:01:58,934:INFO:Copying training dataset +2023-11-09 10:01:58,938:INFO:Defining folds +2023-11-09 10:01:58,938:INFO:Declaring metric variables +2023-11-09 10:01:58,941:INFO:Importing untrained model +2023-11-09 10:01:58,945:INFO:Passive Aggressive Regressor Imported successfully +2023-11-09 10:01:58,950:INFO:Starting cross validation +2023-11-09 10:01:58,951:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:01:59,026:INFO:Calculating mean and std +2023-11-09 10:01:59,026:INFO:Creating metrics dataframe +2023-11-09 10:01:59,029:INFO:Uploading results into container +2023-11-09 10:01:59,029:INFO:Uploading model into container now +2023-11-09 10:01:59,029:INFO:_master_model_container: 9 +2023-11-09 10:01:59,030:INFO:_display_container: 2 +2023-11-09 10:01:59,030:INFO:PassiveAggressiveRegressor(random_state=123) +2023-11-09 10:01:59,030:INFO:create_model() successfully completed...................................... +2023-11-09 10:01:59,121:INFO:SubProcess create_model() end ================================== +2023-11-09 10:01:59,121:INFO:Creating metrics dataframe +2023-11-09 10:01:59,138:INFO:Initializing Huber Regressor +2023-11-09 10:01:59,138:INFO:Total runtime is 0.06928383509318035 minutes +2023-11-09 10:01:59,142:INFO:SubProcess create_model() called ================================== +2023-11-09 10:01:59,142:INFO:Initializing create_model() +2023-11-09 10:01:59,142:INFO:create_model(self=, estimator=huber, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:01:59,142:INFO:Checking exceptions +2023-11-09 10:01:59,142:INFO:Importing libraries +2023-11-09 10:01:59,142:INFO:Copying training dataset +2023-11-09 10:01:59,147:INFO:Defining folds +2023-11-09 10:01:59,147:INFO:Declaring metric variables +2023-11-09 10:01:59,152:INFO:Importing untrained model +2023-11-09 10:01:59,155:INFO:Huber Regressor Imported successfully +2023-11-09 10:01:59,165:INFO:Starting cross validation +2023-11-09 10:01:59,166:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:01:59,294:INFO:Calculating mean and std +2023-11-09 10:01:59,295:INFO:Creating metrics dataframe +2023-11-09 10:01:59,299:INFO:Uploading results into container +2023-11-09 10:01:59,300:INFO:Uploading model into container now +2023-11-09 10:01:59,300:INFO:_master_model_container: 10 +2023-11-09 10:01:59,300:INFO:_display_container: 2 +2023-11-09 10:01:59,301:INFO:HuberRegressor() +2023-11-09 10:01:59,301:INFO:create_model() successfully completed...................................... +2023-11-09 10:01:59,383:INFO:SubProcess create_model() end ================================== +2023-11-09 10:01:59,384:INFO:Creating metrics dataframe +2023-11-09 10:01:59,393:INFO:Initializing K Neighbors Regressor +2023-11-09 10:01:59,393:INFO:Total runtime is 0.07354575792948406 minutes +2023-11-09 10:01:59,397:INFO:SubProcess create_model() called ================================== +2023-11-09 10:01:59,398:INFO:Initializing create_model() +2023-11-09 10:01:59,398:INFO:create_model(self=, estimator=knn, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:01:59,398:INFO:Checking exceptions +2023-11-09 10:01:59,398:INFO:Importing libraries +2023-11-09 10:01:59,398:INFO:Copying training dataset +2023-11-09 10:01:59,401:INFO:Defining folds +2023-11-09 10:01:59,402:INFO:Declaring metric variables +2023-11-09 10:01:59,405:INFO:Importing untrained model +2023-11-09 10:01:59,408:INFO:K Neighbors Regressor Imported successfully +2023-11-09 10:01:59,413:INFO:Starting cross validation +2023-11-09 10:01:59,414:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:01:59,509:INFO:Calculating mean and std +2023-11-09 10:01:59,510:INFO:Creating metrics dataframe +2023-11-09 10:01:59,514:INFO:Uploading results into container +2023-11-09 10:01:59,514:INFO:Uploading model into container now +2023-11-09 10:01:59,515:INFO:_master_model_container: 11 +2023-11-09 10:01:59,515:INFO:_display_container: 2 +2023-11-09 10:01:59,515:INFO:KNeighborsRegressor(n_jobs=-1) +2023-11-09 10:01:59,515:INFO:create_model() successfully completed...................................... +2023-11-09 10:01:59,596:INFO:SubProcess create_model() end ================================== +2023-11-09 10:01:59,596:INFO:Creating metrics dataframe +2023-11-09 10:01:59,606:INFO:Initializing Decision Tree Regressor +2023-11-09 10:01:59,606:INFO:Total runtime is 0.07708897988001506 minutes +2023-11-09 10:01:59,609:INFO:SubProcess create_model() called ================================== +2023-11-09 10:01:59,610:INFO:Initializing create_model() +2023-11-09 10:01:59,610:INFO:create_model(self=, estimator=dt, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:01:59,610:INFO:Checking exceptions +2023-11-09 10:01:59,610:INFO:Importing libraries +2023-11-09 10:01:59,610:INFO:Copying training dataset +2023-11-09 10:01:59,613:INFO:Defining folds +2023-11-09 10:01:59,614:INFO:Declaring metric variables +2023-11-09 10:01:59,616:INFO:Importing untrained model +2023-11-09 10:01:59,619:INFO:Decision Tree Regressor Imported successfully +2023-11-09 10:01:59,625:INFO:Starting cross validation +2023-11-09 10:01:59,626:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:01:59,696:INFO:Calculating mean and std +2023-11-09 10:01:59,696:INFO:Creating metrics dataframe +2023-11-09 10:01:59,700:INFO:Uploading results into container +2023-11-09 10:01:59,700:INFO:Uploading model into container now +2023-11-09 10:01:59,700:INFO:_master_model_container: 12 +2023-11-09 10:01:59,701:INFO:_display_container: 2 +2023-11-09 10:01:59,701:INFO:DecisionTreeRegressor(random_state=123) +2023-11-09 10:01:59,701:INFO:create_model() successfully completed...................................... +2023-11-09 10:01:59,781:INFO:SubProcess create_model() end ================================== +2023-11-09 10:01:59,781:INFO:Creating metrics dataframe +2023-11-09 10:01:59,791:INFO:Initializing Random Forest Regressor +2023-11-09 10:01:59,791:INFO:Total runtime is 0.08017359972000122 minutes +2023-11-09 10:01:59,794:INFO:SubProcess create_model() called ================================== +2023-11-09 10:01:59,795:INFO:Initializing create_model() +2023-11-09 10:01:59,795:INFO:create_model(self=, estimator=rf, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:01:59,795:INFO:Checking exceptions +2023-11-09 10:01:59,795:INFO:Importing libraries +2023-11-09 10:01:59,795:INFO:Copying training dataset +2023-11-09 10:01:59,799:INFO:Defining folds +2023-11-09 10:01:59,799:INFO:Declaring metric variables +2023-11-09 10:01:59,803:INFO:Importing untrained model +2023-11-09 10:01:59,806:INFO:Random Forest Regressor Imported successfully +2023-11-09 10:01:59,812:INFO:Starting cross validation +2023-11-09 10:01:59,813:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:02:00,212:INFO:Calculating mean and std +2023-11-09 10:02:00,213:INFO:Creating metrics dataframe +2023-11-09 10:02:00,217:INFO:Uploading results into container +2023-11-09 10:02:00,217:INFO:Uploading model into container now +2023-11-09 10:02:00,218:INFO:_master_model_container: 13 +2023-11-09 10:02:00,218:INFO:_display_container: 2 +2023-11-09 10:02:00,218:INFO:RandomForestRegressor(n_jobs=-1, random_state=123) +2023-11-09 10:02:00,218:INFO:create_model() successfully completed...................................... +2023-11-09 10:02:00,294:INFO:SubProcess create_model() end ================================== +2023-11-09 10:02:00,295:INFO:Creating metrics dataframe +2023-11-09 10:02:00,306:INFO:Initializing Extra Trees Regressor +2023-11-09 10:02:00,306:INFO:Total runtime is 0.08874882062276204 minutes +2023-11-09 10:02:00,309:INFO:SubProcess create_model() called ================================== +2023-11-09 10:02:00,309:INFO:Initializing create_model() +2023-11-09 10:02:00,309:INFO:create_model(self=, estimator=et, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:02:00,309:INFO:Checking exceptions +2023-11-09 10:02:00,310:INFO:Importing libraries +2023-11-09 10:02:00,310:INFO:Copying training dataset +2023-11-09 10:02:00,312:INFO:Defining folds +2023-11-09 10:02:00,312:INFO:Declaring metric variables +2023-11-09 10:02:00,315:INFO:Importing untrained model +2023-11-09 10:02:00,318:INFO:Extra Trees Regressor Imported successfully +2023-11-09 10:02:00,325:INFO:Starting cross validation +2023-11-09 10:02:00,326:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:02:00,723:INFO:Calculating mean and std +2023-11-09 10:02:00,724:INFO:Creating metrics dataframe +2023-11-09 10:02:00,727:INFO:Uploading results into container +2023-11-09 10:02:00,728:INFO:Uploading model into container now +2023-11-09 10:02:00,729:INFO:_master_model_container: 14 +2023-11-09 10:02:00,729:INFO:_display_container: 2 +2023-11-09 10:02:00,729:INFO:ExtraTreesRegressor(n_jobs=-1, random_state=123) +2023-11-09 10:02:00,730:INFO:create_model() successfully completed...................................... +2023-11-09 10:02:00,805:INFO:SubProcess create_model() end ================================== +2023-11-09 10:02:00,805:INFO:Creating metrics dataframe +2023-11-09 10:02:00,815:INFO:Initializing AdaBoost Regressor +2023-11-09 10:02:00,815:INFO:Total runtime is 0.09724491834640503 minutes +2023-11-09 10:02:00,819:INFO:SubProcess create_model() called ================================== +2023-11-09 10:02:00,819:INFO:Initializing create_model() +2023-11-09 10:02:00,819:INFO:create_model(self=, estimator=ada, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:02:00,819:INFO:Checking exceptions +2023-11-09 10:02:00,819:INFO:Importing libraries +2023-11-09 10:02:00,819:INFO:Copying training dataset +2023-11-09 10:02:00,822:INFO:Defining folds +2023-11-09 10:02:00,822:INFO:Declaring metric variables +2023-11-09 10:02:00,825:INFO:Importing untrained model +2023-11-09 10:02:00,828:INFO:AdaBoost Regressor Imported successfully +2023-11-09 10:02:00,835:INFO:Starting cross validation +2023-11-09 10:02:00,836:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:02:01,027:INFO:Calculating mean and std +2023-11-09 10:02:01,027:INFO:Creating metrics dataframe +2023-11-09 10:02:01,032:INFO:Uploading results into container +2023-11-09 10:02:01,033:INFO:Uploading model into container now +2023-11-09 10:02:01,033:INFO:_master_model_container: 15 +2023-11-09 10:02:01,033:INFO:_display_container: 2 +2023-11-09 10:02:01,034:INFO:AdaBoostRegressor(random_state=123) +2023-11-09 10:02:01,034:INFO:create_model() successfully completed...................................... +2023-11-09 10:02:01,115:INFO:SubProcess create_model() end ================================== +2023-11-09 10:02:01,115:INFO:Creating metrics dataframe +2023-11-09 10:02:01,125:INFO:Initializing Gradient Boosting Regressor +2023-11-09 10:02:01,125:INFO:Total runtime is 0.10240623950958253 minutes +2023-11-09 10:02:01,128:INFO:SubProcess create_model() called ================================== +2023-11-09 10:02:01,129:INFO:Initializing create_model() +2023-11-09 10:02:01,129:INFO:create_model(self=, estimator=gbr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:02:01,129:INFO:Checking exceptions +2023-11-09 10:02:01,129:INFO:Importing libraries +2023-11-09 10:02:01,129:INFO:Copying training dataset +2023-11-09 10:02:01,132:INFO:Defining folds +2023-11-09 10:02:01,132:INFO:Declaring metric variables +2023-11-09 10:02:01,134:INFO:Importing untrained model +2023-11-09 10:02:01,137:INFO:Gradient Boosting Regressor Imported successfully +2023-11-09 10:02:01,144:INFO:Starting cross validation +2023-11-09 10:02:01,145:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:02:01,296:INFO:Calculating mean and std +2023-11-09 10:02:01,296:INFO:Creating metrics dataframe +2023-11-09 10:02:01,300:INFO:Uploading results into container +2023-11-09 10:02:01,300:INFO:Uploading model into container now +2023-11-09 10:02:01,301:INFO:_master_model_container: 16 +2023-11-09 10:02:01,301:INFO:_display_container: 2 +2023-11-09 10:02:01,301:INFO:GradientBoostingRegressor(random_state=123) +2023-11-09 10:02:01,301:INFO:create_model() successfully completed...................................... +2023-11-09 10:02:01,380:INFO:SubProcess create_model() end ================================== +2023-11-09 10:02:01,380:INFO:Creating metrics dataframe +2023-11-09 10:02:01,391:INFO:Initializing Light Gradient Boosting Machine +2023-11-09 10:02:01,391:INFO:Total runtime is 0.10683684349060059 minutes +2023-11-09 10:02:01,394:INFO:SubProcess create_model() called ================================== +2023-11-09 10:02:01,395:INFO:Initializing create_model() +2023-11-09 10:02:01,395:INFO:create_model(self=, estimator=lightgbm, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:02:01,395:INFO:Checking exceptions +2023-11-09 10:02:01,395:INFO:Importing libraries +2023-11-09 10:02:01,395:INFO:Copying training dataset +2023-11-09 10:02:01,397:INFO:Defining folds +2023-11-09 10:02:01,398:INFO:Declaring metric variables +2023-11-09 10:02:01,400:INFO:Importing untrained model +2023-11-09 10:02:01,404:INFO:Light Gradient Boosting Machine Imported successfully +2023-11-09 10:02:01,411:INFO:Starting cross validation +2023-11-09 10:02:01,412:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:02:02,039:INFO:Calculating mean and std +2023-11-09 10:02:02,039:INFO:Creating metrics dataframe +2023-11-09 10:02:02,043:INFO:Uploading results into container +2023-11-09 10:02:02,044:INFO:Uploading model into container now +2023-11-09 10:02:02,045:INFO:_master_model_container: 17 +2023-11-09 10:02:02,045:INFO:_display_container: 2 +2023-11-09 10:02:02,045:INFO:LGBMRegressor(n_jobs=-1, random_state=123) +2023-11-09 10:02:02,045:INFO:create_model() successfully completed...................................... +2023-11-09 10:02:02,155:INFO:SubProcess create_model() end ================================== +2023-11-09 10:02:02,156:INFO:Creating metrics dataframe +2023-11-09 10:02:02,167:INFO:Initializing Dummy Regressor +2023-11-09 10:02:02,168:INFO:Total runtime is 0.1197807788848877 minutes +2023-11-09 10:02:02,171:INFO:SubProcess create_model() called ================================== +2023-11-09 10:02:02,171:INFO:Initializing create_model() +2023-11-09 10:02:02,172:INFO:create_model(self=, estimator=dummy, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:02:02,172:INFO:Checking exceptions +2023-11-09 10:02:02,172:INFO:Importing libraries +2023-11-09 10:02:02,172:INFO:Copying training dataset +2023-11-09 10:02:02,174:INFO:Defining folds +2023-11-09 10:02:02,174:INFO:Declaring metric variables +2023-11-09 10:02:02,177:INFO:Importing untrained model +2023-11-09 10:02:02,180:INFO:Dummy Regressor Imported successfully +2023-11-09 10:02:02,187:INFO:Starting cross validation +2023-11-09 10:02:02,188:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:02:02,255:INFO:Calculating mean and std +2023-11-09 10:02:02,255:INFO:Creating metrics dataframe +2023-11-09 10:02:02,258:INFO:Uploading results into container +2023-11-09 10:02:02,259:INFO:Uploading model into container now +2023-11-09 10:02:02,259:INFO:_master_model_container: 18 +2023-11-09 10:02:02,259:INFO:_display_container: 2 +2023-11-09 10:02:02,259:INFO:DummyRegressor() +2023-11-09 10:02:02,259:INFO:create_model() successfully completed...................................... +2023-11-09 10:02:02,368:INFO:SubProcess create_model() end ================================== +2023-11-09 10:02:02,368:INFO:Creating metrics dataframe +2023-11-09 10:02:02,390:INFO:Initializing create_model() +2023-11-09 10:02:02,390:INFO:create_model(self=, estimator=HuberRegressor(), fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=False, predict=False, fit_kwargs={}, groups=None, refit=True, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=None, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:02:02,390:INFO:Checking exceptions +2023-11-09 10:02:02,392:INFO:Importing libraries +2023-11-09 10:02:02,392:INFO:Copying training dataset +2023-11-09 10:02:02,395:INFO:Defining folds +2023-11-09 10:02:02,395:INFO:Declaring metric variables +2023-11-09 10:02:02,396:INFO:Importing untrained model +2023-11-09 10:02:02,396:INFO:Declaring custom model +2023-11-09 10:02:02,396:INFO:Huber Regressor Imported successfully +2023-11-09 10:02:02,397:INFO:Cross validation set to False +2023-11-09 10:02:02,397:INFO:Fitting Model +2023-11-09 10:02:02,421:INFO:HuberRegressor() +2023-11-09 10:02:02,421:INFO:create_model() successfully completed...................................... +2023-11-09 10:02:02,529:INFO:_master_model_container: 18 +2023-11-09 10:02:02,529:INFO:_display_container: 2 +2023-11-09 10:02:02,529:INFO:HuberRegressor() +2023-11-09 10:02:02,529:INFO:compare_models() successfully completed...................................... +2023-11-09 10:44:47,260:WARNING: +'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. +2023-11-09 10:44:47,261:WARNING: +'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. +2023-11-09 10:44:47,261:WARNING: +'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. +2023-11-09 10:44:47,261:WARNING: +'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. +2023-11-09 10:44:47,596:INFO:PyCaret RegressionExperiment +2023-11-09 10:44:47,598:INFO:Logging name: reg-default-name +2023-11-09 10:44:47,598:INFO:ML Usecase: MLUsecase.REGRESSION +2023-11-09 10:44:47,598:INFO:version 3.1.0 +2023-11-09 10:44:47,599:INFO:Initializing setup() +2023-11-09 10:44:47,599:INFO:self.USI: 005c +2023-11-09 10:44:47,600:INFO:self._variable_keys: {'seed', 'idx', 'transform_target_param', 'gpu_param', 'target_param', 'log_plots_param', 'pipeline', 'logging_param', 'fold_groups_param', '_ml_usecase', 'html_param', 'gpu_n_jobs_param', 'y', 'y_test', 'y_train', 'memory', 'exp_id', 'X_test', 'exp_name_log', 'USI', 'data', 'X_train', 'fold_shuffle_param', 'X', 'fold_generator', 'n_jobs_param', '_available_plots'} +2023-11-09 10:44:47,600:INFO:Checking environment +2023-11-09 10:44:47,600:INFO:python_version: 3.8.18 +2023-11-09 10:44:47,600:INFO:python_build: ('default', 'Sep 11 2023 13:40:15') +2023-11-09 10:44:47,601:INFO:machine: x86_64 +2023-11-09 10:44:47,601:INFO:platform: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 10:44:47,601:INFO:Memory: svmem(total=8315187200, available=5218893824, percent=37.2, used=2761687040, free=524611584, active=1463525376, inactive=5511421952, buffers=334630912, cached=4694257664, shared=4448256, slab=649134080) +2023-11-09 10:44:47,602:INFO:Physical Core: 1 +2023-11-09 10:44:47,602:INFO:Logical Core: 2 +2023-11-09 10:44:47,602:INFO:Checking libraries +2023-11-09 10:44:47,603:INFO:System: +2023-11-09 10:44:47,603:INFO: python: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] +2023-11-09 10:44:47,606:INFO:executable: /workspaces/D2I-Jupyter-Notebook-Tools/.conda/bin/python +2023-11-09 10:44:47,607:INFO: machine: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 10:44:47,607:INFO:PyCaret required dependencies: +2023-11-09 10:44:47,684:INFO: pip: 23.3 +2023-11-09 10:44:47,684:INFO: setuptools: 68.0.0 +2023-11-09 10:44:47,684:INFO: pycaret: 3.1.0 +2023-11-09 10:44:47,684:INFO: IPython: 8.12.0 +2023-11-09 10:44:47,684:INFO: ipywidgets: 8.1.1 +2023-11-09 10:44:47,684:INFO: tqdm: 4.66.1 +2023-11-09 10:44:47,684:INFO: numpy: 1.23.5 +2023-11-09 10:44:47,684:INFO: pandas: 1.5.3 +2023-11-09 10:44:47,684:INFO: jinja2: 3.1.2 +2023-11-09 10:44:47,684:INFO: scipy: 1.10.1 +2023-11-09 10:44:47,685:INFO: joblib: 1.3.2 +2023-11-09 10:44:47,685:INFO: sklearn: 1.2.2 +2023-11-09 10:44:47,685:INFO: pyod: 1.1.1 +2023-11-09 10:44:47,685:INFO: imblearn: 0.11.0 +2023-11-09 10:44:47,685:INFO: category_encoders: 2.6.3 +2023-11-09 10:44:47,686:INFO: lightgbm: 4.1.0 +2023-11-09 10:44:47,686:INFO: numba: 0.58.1 +2023-11-09 10:44:47,686:INFO: requests: 2.31.0 +2023-11-09 10:44:47,686:INFO: matplotlib: 3.7.3 +2023-11-09 10:44:47,686:INFO: scikitplot: 0.3.7 +2023-11-09 10:44:47,686:INFO: yellowbrick: 1.5 +2023-11-09 10:44:47,686:INFO: plotly: 5.18.0 +2023-11-09 10:44:47,686:INFO: plotly-resampler: Not installed +2023-11-09 10:44:47,687:INFO: kaleido: 0.2.1 +2023-11-09 10:44:47,687:INFO: schemdraw: 0.15 +2023-11-09 10:44:47,687:INFO: statsmodels: 0.14.0 +2023-11-09 10:44:47,687:INFO: sktime: 0.21.1 +2023-11-09 10:44:47,687:INFO: tbats: 1.1.3 +2023-11-09 10:44:47,687:INFO: pmdarima: 2.0.4 +2023-11-09 10:44:47,687:INFO: psutil: 5.9.0 +2023-11-09 10:44:47,687:INFO: markupsafe: 2.1.3 +2023-11-09 10:44:47,687:INFO: pickle5: Not installed +2023-11-09 10:44:47,687:INFO: cloudpickle: 3.0.0 +2023-11-09 10:44:47,687:INFO: deprecation: 2.1.0 +2023-11-09 10:44:47,687:INFO: xxhash: 3.4.1 +2023-11-09 10:44:47,687:INFO: wurlitzer: 3.0.3 +2023-11-09 10:44:47,688:INFO:PyCaret optional dependencies: +2023-11-09 10:44:47,711:INFO: shap: Not installed +2023-11-09 10:44:47,711:INFO: interpret: Not installed +2023-11-09 10:44:47,711:INFO: umap: Not installed +2023-11-09 10:44:47,711:INFO: ydata_profiling: Not installed +2023-11-09 10:44:47,711:INFO: explainerdashboard: Not installed +2023-11-09 10:44:47,712:INFO: autoviz: Not installed +2023-11-09 10:44:47,712:INFO: fairlearn: Not installed +2023-11-09 10:44:47,712:INFO: deepchecks: Not installed +2023-11-09 10:44:47,712:INFO: xgboost: Not installed +2023-11-09 10:44:47,712:INFO: catboost: Not installed +2023-11-09 10:44:47,712:INFO: kmodes: Not installed +2023-11-09 10:44:47,713:INFO: mlxtend: Not installed +2023-11-09 10:44:47,713:INFO: statsforecast: Not installed +2023-11-09 10:44:47,713:INFO: tune_sklearn: Not installed +2023-11-09 10:44:47,713:INFO: ray: Not installed +2023-11-09 10:44:47,713:INFO: hyperopt: Not installed +2023-11-09 10:44:47,713:INFO: optuna: Not installed +2023-11-09 10:44:47,714:INFO: skopt: Not installed +2023-11-09 10:44:47,714:INFO: mlflow: Not installed +2023-11-09 10:44:47,714:INFO: gradio: Not installed +2023-11-09 10:44:47,714:INFO: fastapi: Not installed +2023-11-09 10:44:47,714:INFO: uvicorn: Not installed +2023-11-09 10:44:47,714:INFO: m2cgen: Not installed +2023-11-09 10:44:47,715:INFO: evidently: Not installed +2023-11-09 10:44:47,715:INFO: fugue: Not installed +2023-11-09 10:44:47,715:INFO: streamlit: Not installed +2023-11-09 10:44:47,715:INFO: prophet: Not installed +2023-11-09 10:44:47,716:INFO:None +2023-11-09 10:44:47,716:INFO:Set up data. +2023-11-09 10:44:47,724:INFO:Set up folding strategy. +2023-11-09 10:44:47,724:INFO:Set up train/test split. +2023-11-09 10:44:47,724:INFO:Set up data. +2023-11-09 10:44:47,729:INFO:Set up index. +2023-11-09 10:44:47,730:INFO:Assigning column types. +2023-11-09 10:44:47,736:INFO:Engine successfully changes for model 'lr' to 'sklearn'. +2023-11-09 10:44:47,737:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 10:44:47,744:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 10:44:47,751:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 10:44:47,871:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:44:47,936:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:44:47,937:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:47,938:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:47,939:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 10:44:47,944:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 10:44:47,951:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 10:44:48,055:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:44:48,201:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:44:48,207:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:48,208:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:48,208:INFO:Engine successfully changes for model 'lasso' to 'sklearn'. +2023-11-09 10:44:48,222:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 10:44:48,247:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 10:44:48,370:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:44:48,469:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:44:48,471:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:48,473:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:48,487:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 10:44:48,495:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 10:44:48,621:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:44:48,762:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:44:48,763:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:48,764:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:48,765:INFO:Engine successfully changes for model 'ridge' to 'sklearn'. +2023-11-09 10:44:48,780:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 10:44:48,910:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:44:48,993:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:44:48,994:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:48,994:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,010:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 10:44:49,113:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:44:49,293:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:44:49,303:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,304:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,304:INFO:Engine successfully changes for model 'en' to 'sklearn'. +2023-11-09 10:44:49,446:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:44:49,489:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:44:49,490:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,490:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,547:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:44:49,585:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 10:44:49,586:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,586:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,587:INFO:Engine successfully changes for model 'knn' to 'sklearn'. +2023-11-09 10:44:49,646:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:44:49,685:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,685:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,744:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 10:44:49,782:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,783:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,783:INFO:Engine successfully changes for model 'svm' to 'sklearn'. +2023-11-09 10:44:49,881:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,881:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,983:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,983:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:49,984:INFO:Preparing preprocessing pipeline... +2023-11-09 10:44:49,984:INFO:Set up target transformation. +2023-11-09 10:44:49,984:INFO:Set up simple imputation. +2023-11-09 10:44:49,985:INFO:Set up column name cleaning. +2023-11-09 10:44:50,013:INFO:Finished creating preprocessing pipeline. +2023-11-09 10:44:50,020:INFO:Pipeline: Pipeline(memory=FastMemory(location=/tmp/joblib), + steps=[('target_transformation', + TransformerWrapperWithInverse(transformer=TargetTransformer(estimator=PowerTransformer(standardize=False)))), + ('numerical_imputer', + TransformerWrapper(include=['Year', 'Series'], + transformer=SimpleImputer())), + ('categorical_imputer', + TransformerWrapper(include=[], + transformer=SimpleImputer(strategy='most_frequent'))), + ('clean_column_names', + TransformerWrapper(transformer=CleanColumnNames()))]) +2023-11-09 10:44:50,020:INFO:Creating final display dataframe. +2023-11-09 10:44:50,121:INFO:Setup _display_container: Description Value +0 Session id 123 +1 Target Average price All property types +2 Target type Regression +3 Original data shape (523, 4) +4 Transformed data shape (523, 4) +5 Transformed train set shape (372, 4) +6 Transformed test set shape (151, 4) +7 Numeric features 2 +8 Preprocess True +9 Imputation type simple +10 Numeric imputation mean +11 Categorical imputation mode +12 Transform target True +13 Transform target method yeo-johnson +14 Fold Generator TimeSeriesSplit +15 Fold Number 3 +16 CPU Jobs -1 +17 Use GPU False +18 Log Experiment False +19 Experiment Name reg-default-name +20 USI 005c +2023-11-09 10:44:50,314:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:50,315:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:50,417:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:50,417:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 10:44:50,418:INFO:setup() successfully completed in 2.82s............... +2023-11-09 10:44:50,425:INFO:Initializing compare_models() +2023-11-09 10:44:50,426:INFO:compare_models(self=, include=None, fold=None, round=4, cross_validation=True, sort=MAE, n_select=1, budget_time=None, turbo=True, errors=ignore, fit_kwargs=None, groups=None, experiment_custom_tags=None, probability_threshold=None, verbose=True, parallel=None, caller_params={'self': , 'include': None, 'exclude': None, 'fold': None, 'round': 4, 'cross_validation': True, 'sort': 'MAE', 'n_select': 1, 'budget_time': None, 'turbo': True, 'errors': 'ignore', 'fit_kwargs': None, 'groups': None, 'experiment_custom_tags': None, 'engine': None, 'verbose': True, 'parallel': None, '__class__': }, exclude=None) +2023-11-09 10:44:50,426:INFO:Checking exceptions +2023-11-09 10:44:50,428:INFO:Preparing display monitor +2023-11-09 10:44:50,454:INFO:Initializing Linear Regression +2023-11-09 10:44:50,455:INFO:Total runtime is 8.821487426757812e-06 minutes +2023-11-09 10:44:50,459:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:50,459:INFO:Initializing create_model() +2023-11-09 10:44:50,460:INFO:create_model(self=, estimator=lr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:50,460:INFO:Checking exceptions +2023-11-09 10:44:50,460:INFO:Importing libraries +2023-11-09 10:44:50,460:INFO:Copying training dataset +2023-11-09 10:44:50,464:INFO:Defining folds +2023-11-09 10:44:50,464:INFO:Declaring metric variables +2023-11-09 10:44:50,467:INFO:Importing untrained model +2023-11-09 10:44:50,474:INFO:Linear Regression Imported successfully +2023-11-09 10:44:50,483:INFO:Starting cross validation +2023-11-09 10:44:50,486:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:52,602:INFO:Calculating mean and std +2023-11-09 10:44:52,604:INFO:Creating metrics dataframe +2023-11-09 10:44:52,610:INFO:Uploading results into container +2023-11-09 10:44:52,611:INFO:Uploading model into container now +2023-11-09 10:44:52,612:INFO:_master_model_container: 1 +2023-11-09 10:44:52,612:INFO:_display_container: 2 +2023-11-09 10:44:52,612:INFO:LinearRegression(n_jobs=-1) +2023-11-09 10:44:52,613:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:52,718:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:52,719:INFO:Creating metrics dataframe +2023-11-09 10:44:52,733:INFO:Initializing Lasso Regression +2023-11-09 10:44:52,733:INFO:Total runtime is 0.03797665039698283 minutes +2023-11-09 10:44:52,738:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:52,738:INFO:Initializing create_model() +2023-11-09 10:44:52,738:INFO:create_model(self=, estimator=lasso, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:52,738:INFO:Checking exceptions +2023-11-09 10:44:52,739:INFO:Importing libraries +2023-11-09 10:44:52,739:INFO:Copying training dataset +2023-11-09 10:44:52,744:INFO:Defining folds +2023-11-09 10:44:52,745:INFO:Declaring metric variables +2023-11-09 10:44:52,751:INFO:Importing untrained model +2023-11-09 10:44:52,756:INFO:Lasso Regression Imported successfully +2023-11-09 10:44:52,767:INFO:Starting cross validation +2023-11-09 10:44:52,768:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:52,855:INFO:Calculating mean and std +2023-11-09 10:44:52,856:INFO:Creating metrics dataframe +2023-11-09 10:44:52,860:INFO:Uploading results into container +2023-11-09 10:44:52,861:INFO:Uploading model into container now +2023-11-09 10:44:52,861:INFO:_master_model_container: 2 +2023-11-09 10:44:52,861:INFO:_display_container: 2 +2023-11-09 10:44:52,862:INFO:Lasso(random_state=123) +2023-11-09 10:44:52,862:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:52,941:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:52,942:INFO:Creating metrics dataframe +2023-11-09 10:44:52,950:INFO:Initializing Ridge Regression +2023-11-09 10:44:52,951:INFO:Total runtime is 0.04160174528757731 minutes +2023-11-09 10:44:52,954:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:52,954:INFO:Initializing create_model() +2023-11-09 10:44:52,955:INFO:create_model(self=, estimator=ridge, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:52,955:INFO:Checking exceptions +2023-11-09 10:44:52,955:INFO:Importing libraries +2023-11-09 10:44:52,955:INFO:Copying training dataset +2023-11-09 10:44:52,961:INFO:Defining folds +2023-11-09 10:44:52,961:INFO:Declaring metric variables +2023-11-09 10:44:52,965:INFO:Importing untrained model +2023-11-09 10:44:52,969:INFO:Ridge Regression Imported successfully +2023-11-09 10:44:52,975:INFO:Starting cross validation +2023-11-09 10:44:52,976:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:53,056:INFO:Calculating mean and std +2023-11-09 10:44:53,056:INFO:Creating metrics dataframe +2023-11-09 10:44:53,061:INFO:Uploading results into container +2023-11-09 10:44:53,062:INFO:Uploading model into container now +2023-11-09 10:44:53,062:INFO:_master_model_container: 3 +2023-11-09 10:44:53,063:INFO:_display_container: 2 +2023-11-09 10:44:53,063:INFO:Ridge(random_state=123) +2023-11-09 10:44:53,063:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:53,140:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:53,140:INFO:Creating metrics dataframe +2023-11-09 10:44:53,148:INFO:Initializing Elastic Net +2023-11-09 10:44:53,149:INFO:Total runtime is 0.044902992248535153 minutes +2023-11-09 10:44:53,152:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:53,153:INFO:Initializing create_model() +2023-11-09 10:44:53,153:INFO:create_model(self=, estimator=en, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:53,153:INFO:Checking exceptions +2023-11-09 10:44:53,153:INFO:Importing libraries +2023-11-09 10:44:53,153:INFO:Copying training dataset +2023-11-09 10:44:53,156:INFO:Defining folds +2023-11-09 10:44:53,157:INFO:Declaring metric variables +2023-11-09 10:44:53,160:INFO:Importing untrained model +2023-11-09 10:44:53,163:INFO:Elastic Net Imported successfully +2023-11-09 10:44:53,169:INFO:Starting cross validation +2023-11-09 10:44:53,171:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:53,252:INFO:Calculating mean and std +2023-11-09 10:44:53,253:INFO:Creating metrics dataframe +2023-11-09 10:44:53,260:INFO:Uploading results into container +2023-11-09 10:44:53,261:INFO:Uploading model into container now +2023-11-09 10:44:53,261:INFO:_master_model_container: 4 +2023-11-09 10:44:53,262:INFO:_display_container: 2 +2023-11-09 10:44:53,262:INFO:ElasticNet(random_state=123) +2023-11-09 10:44:53,262:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:53,345:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:53,345:INFO:Creating metrics dataframe +2023-11-09 10:44:53,354:INFO:Initializing Least Angle Regression +2023-11-09 10:44:53,354:INFO:Total runtime is 0.04832832018534342 minutes +2023-11-09 10:44:53,357:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:53,357:INFO:Initializing create_model() +2023-11-09 10:44:53,358:INFO:create_model(self=, estimator=lar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:53,358:INFO:Checking exceptions +2023-11-09 10:44:53,358:INFO:Importing libraries +2023-11-09 10:44:53,358:INFO:Copying training dataset +2023-11-09 10:44:53,363:INFO:Defining folds +2023-11-09 10:44:53,364:INFO:Declaring metric variables +2023-11-09 10:44:53,368:INFO:Importing untrained model +2023-11-09 10:44:53,373:INFO:Least Angle Regression Imported successfully +2023-11-09 10:44:53,378:INFO:Starting cross validation +2023-11-09 10:44:53,380:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:53,458:INFO:Calculating mean and std +2023-11-09 10:44:53,458:INFO:Creating metrics dataframe +2023-11-09 10:44:53,461:INFO:Uploading results into container +2023-11-09 10:44:53,462:INFO:Uploading model into container now +2023-11-09 10:44:53,462:INFO:_master_model_container: 5 +2023-11-09 10:44:53,462:INFO:_display_container: 2 +2023-11-09 10:44:53,463:INFO:Lars(random_state=123) +2023-11-09 10:44:53,463:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:53,539:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:53,540:INFO:Creating metrics dataframe +2023-11-09 10:44:53,548:INFO:Initializing Lasso Least Angle Regression +2023-11-09 10:44:53,549:INFO:Total runtime is 0.0515765905380249 minutes +2023-11-09 10:44:53,553:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:53,554:INFO:Initializing create_model() +2023-11-09 10:44:53,554:INFO:create_model(self=, estimator=llar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:53,554:INFO:Checking exceptions +2023-11-09 10:44:53,554:INFO:Importing libraries +2023-11-09 10:44:53,554:INFO:Copying training dataset +2023-11-09 10:44:53,558:INFO:Defining folds +2023-11-09 10:44:53,558:INFO:Declaring metric variables +2023-11-09 10:44:53,562:INFO:Importing untrained model +2023-11-09 10:44:53,566:INFO:Lasso Least Angle Regression Imported successfully +2023-11-09 10:44:53,571:INFO:Starting cross validation +2023-11-09 10:44:53,573:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:53,659:INFO:Calculating mean and std +2023-11-09 10:44:53,660:INFO:Creating metrics dataframe +2023-11-09 10:44:53,663:INFO:Uploading results into container +2023-11-09 10:44:53,665:INFO:Uploading model into container now +2023-11-09 10:44:53,665:INFO:_master_model_container: 6 +2023-11-09 10:44:53,665:INFO:_display_container: 2 +2023-11-09 10:44:53,666:INFO:LassoLars(random_state=123) +2023-11-09 10:44:53,666:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:53,744:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:53,744:INFO:Creating metrics dataframe +2023-11-09 10:44:53,753:INFO:Initializing Orthogonal Matching Pursuit +2023-11-09 10:44:53,753:INFO:Total runtime is 0.05497572422027588 minutes +2023-11-09 10:44:53,757:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:53,757:INFO:Initializing create_model() +2023-11-09 10:44:53,757:INFO:create_model(self=, estimator=omp, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:53,758:INFO:Checking exceptions +2023-11-09 10:44:53,758:INFO:Importing libraries +2023-11-09 10:44:53,758:INFO:Copying training dataset +2023-11-09 10:44:53,762:INFO:Defining folds +2023-11-09 10:44:53,762:INFO:Declaring metric variables +2023-11-09 10:44:53,766:INFO:Importing untrained model +2023-11-09 10:44:53,769:INFO:Orthogonal Matching Pursuit Imported successfully +2023-11-09 10:44:53,776:INFO:Starting cross validation +2023-11-09 10:44:53,777:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:53,855:INFO:Calculating mean and std +2023-11-09 10:44:53,855:INFO:Creating metrics dataframe +2023-11-09 10:44:53,859:INFO:Uploading results into container +2023-11-09 10:44:53,859:INFO:Uploading model into container now +2023-11-09 10:44:53,860:INFO:_master_model_container: 7 +2023-11-09 10:44:53,860:INFO:_display_container: 2 +2023-11-09 10:44:53,860:INFO:OrthogonalMatchingPursuit() +2023-11-09 10:44:53,860:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:53,936:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:53,936:INFO:Creating metrics dataframe +2023-11-09 10:44:53,945:INFO:Initializing Bayesian Ridge +2023-11-09 10:44:53,945:INFO:Total runtime is 0.05818490584691365 minutes +2023-11-09 10:44:53,949:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:53,949:INFO:Initializing create_model() +2023-11-09 10:44:53,949:INFO:create_model(self=, estimator=br, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:53,950:INFO:Checking exceptions +2023-11-09 10:44:53,950:INFO:Importing libraries +2023-11-09 10:44:53,950:INFO:Copying training dataset +2023-11-09 10:44:53,954:INFO:Defining folds +2023-11-09 10:44:53,955:INFO:Declaring metric variables +2023-11-09 10:44:53,958:INFO:Importing untrained model +2023-11-09 10:44:53,963:INFO:Bayesian Ridge Imported successfully +2023-11-09 10:44:53,969:INFO:Starting cross validation +2023-11-09 10:44:53,970:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:54,049:INFO:Calculating mean and std +2023-11-09 10:44:54,049:INFO:Creating metrics dataframe +2023-11-09 10:44:54,052:INFO:Uploading results into container +2023-11-09 10:44:54,053:INFO:Uploading model into container now +2023-11-09 10:44:54,053:INFO:_master_model_container: 8 +2023-11-09 10:44:54,053:INFO:_display_container: 2 +2023-11-09 10:44:54,054:INFO:BayesianRidge() +2023-11-09 10:44:54,054:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:54,130:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:54,130:INFO:Creating metrics dataframe +2023-11-09 10:44:54,139:INFO:Initializing Passive Aggressive Regressor +2023-11-09 10:44:54,140:INFO:Total runtime is 0.06142244736353556 minutes +2023-11-09 10:44:54,143:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:54,144:INFO:Initializing create_model() +2023-11-09 10:44:54,144:INFO:create_model(self=, estimator=par, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:54,144:INFO:Checking exceptions +2023-11-09 10:44:54,144:INFO:Importing libraries +2023-11-09 10:44:54,144:INFO:Copying training dataset +2023-11-09 10:44:54,147:INFO:Defining folds +2023-11-09 10:44:54,148:INFO:Declaring metric variables +2023-11-09 10:44:54,151:INFO:Importing untrained model +2023-11-09 10:44:54,154:INFO:Passive Aggressive Regressor Imported successfully +2023-11-09 10:44:54,161:INFO:Starting cross validation +2023-11-09 10:44:54,162:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:54,252:INFO:Calculating mean and std +2023-11-09 10:44:54,252:INFO:Creating metrics dataframe +2023-11-09 10:44:54,256:INFO:Uploading results into container +2023-11-09 10:44:54,257:INFO:Uploading model into container now +2023-11-09 10:44:54,257:INFO:_master_model_container: 9 +2023-11-09 10:44:54,257:INFO:_display_container: 2 +2023-11-09 10:44:54,258:INFO:PassiveAggressiveRegressor(random_state=123) +2023-11-09 10:44:54,258:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:54,339:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:54,339:INFO:Creating metrics dataframe +2023-11-09 10:44:54,351:INFO:Initializing Huber Regressor +2023-11-09 10:44:54,351:INFO:Total runtime is 0.064950164159139 minutes +2023-11-09 10:44:54,356:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:54,357:INFO:Initializing create_model() +2023-11-09 10:44:54,357:INFO:create_model(self=, estimator=huber, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:54,357:INFO:Checking exceptions +2023-11-09 10:44:54,357:INFO:Importing libraries +2023-11-09 10:44:54,357:INFO:Copying training dataset +2023-11-09 10:44:54,362:INFO:Defining folds +2023-11-09 10:44:54,362:INFO:Declaring metric variables +2023-11-09 10:44:54,366:INFO:Importing untrained model +2023-11-09 10:44:54,371:INFO:Huber Regressor Imported successfully +2023-11-09 10:44:54,377:INFO:Starting cross validation +2023-11-09 10:44:54,379:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:54,575:INFO:Calculating mean and std +2023-11-09 10:44:54,577:INFO:Creating metrics dataframe +2023-11-09 10:44:54,582:INFO:Uploading results into container +2023-11-09 10:44:54,582:INFO:Uploading model into container now +2023-11-09 10:44:54,582:INFO:_master_model_container: 10 +2023-11-09 10:44:54,583:INFO:_display_container: 2 +2023-11-09 10:44:54,583:INFO:HuberRegressor() +2023-11-09 10:44:54,583:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:54,662:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:54,663:INFO:Creating metrics dataframe +2023-11-09 10:44:54,673:INFO:Initializing K Neighbors Regressor +2023-11-09 10:44:54,673:INFO:Total runtime is 0.07030820846557617 minutes +2023-11-09 10:44:54,676:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:54,677:INFO:Initializing create_model() +2023-11-09 10:44:54,677:INFO:create_model(self=, estimator=knn, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:54,677:INFO:Checking exceptions +2023-11-09 10:44:54,677:INFO:Importing libraries +2023-11-09 10:44:54,677:INFO:Copying training dataset +2023-11-09 10:44:54,681:INFO:Defining folds +2023-11-09 10:44:54,681:INFO:Declaring metric variables +2023-11-09 10:44:54,684:INFO:Importing untrained model +2023-11-09 10:44:54,688:INFO:K Neighbors Regressor Imported successfully +2023-11-09 10:44:54,694:INFO:Starting cross validation +2023-11-09 10:44:54,695:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:54,803:INFO:Calculating mean and std +2023-11-09 10:44:54,805:INFO:Creating metrics dataframe +2023-11-09 10:44:54,809:INFO:Uploading results into container +2023-11-09 10:44:54,810:INFO:Uploading model into container now +2023-11-09 10:44:54,810:INFO:_master_model_container: 11 +2023-11-09 10:44:54,810:INFO:_display_container: 2 +2023-11-09 10:44:54,811:INFO:KNeighborsRegressor(n_jobs=-1) +2023-11-09 10:44:54,811:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:54,906:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:54,906:INFO:Creating metrics dataframe +2023-11-09 10:44:54,921:INFO:Initializing Decision Tree Regressor +2023-11-09 10:44:54,922:INFO:Total runtime is 0.07445542017618816 minutes +2023-11-09 10:44:54,926:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:54,926:INFO:Initializing create_model() +2023-11-09 10:44:54,926:INFO:create_model(self=, estimator=dt, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:54,926:INFO:Checking exceptions +2023-11-09 10:44:54,926:INFO:Importing libraries +2023-11-09 10:44:54,926:INFO:Copying training dataset +2023-11-09 10:44:54,933:INFO:Defining folds +2023-11-09 10:44:54,934:INFO:Declaring metric variables +2023-11-09 10:44:54,939:INFO:Importing untrained model +2023-11-09 10:44:54,943:INFO:Decision Tree Regressor Imported successfully +2023-11-09 10:44:54,952:INFO:Starting cross validation +2023-11-09 10:44:54,953:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:55,054:INFO:Calculating mean and std +2023-11-09 10:44:55,056:INFO:Creating metrics dataframe +2023-11-09 10:44:55,060:INFO:Uploading results into container +2023-11-09 10:44:55,061:INFO:Uploading model into container now +2023-11-09 10:44:55,061:INFO:_master_model_container: 12 +2023-11-09 10:44:55,061:INFO:_display_container: 2 +2023-11-09 10:44:55,062:INFO:DecisionTreeRegressor(random_state=123) +2023-11-09 10:44:55,062:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:55,141:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:55,141:INFO:Creating metrics dataframe +2023-11-09 10:44:55,151:INFO:Initializing Random Forest Regressor +2023-11-09 10:44:55,151:INFO:Total runtime is 0.07827664216359456 minutes +2023-11-09 10:44:55,155:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:55,155:INFO:Initializing create_model() +2023-11-09 10:44:55,155:INFO:create_model(self=, estimator=rf, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:55,156:INFO:Checking exceptions +2023-11-09 10:44:55,156:INFO:Importing libraries +2023-11-09 10:44:55,156:INFO:Copying training dataset +2023-11-09 10:44:55,159:INFO:Defining folds +2023-11-09 10:44:55,160:INFO:Declaring metric variables +2023-11-09 10:44:55,164:INFO:Importing untrained model +2023-11-09 10:44:55,167:INFO:Random Forest Regressor Imported successfully +2023-11-09 10:44:55,174:INFO:Starting cross validation +2023-11-09 10:44:55,175:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:55,667:INFO:Calculating mean and std +2023-11-09 10:44:55,668:INFO:Creating metrics dataframe +2023-11-09 10:44:55,672:INFO:Uploading results into container +2023-11-09 10:44:55,672:INFO:Uploading model into container now +2023-11-09 10:44:55,673:INFO:_master_model_container: 13 +2023-11-09 10:44:55,673:INFO:_display_container: 2 +2023-11-09 10:44:55,674:INFO:RandomForestRegressor(n_jobs=-1, random_state=123) +2023-11-09 10:44:55,674:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:55,751:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:55,752:INFO:Creating metrics dataframe +2023-11-09 10:44:55,762:INFO:Initializing Extra Trees Regressor +2023-11-09 10:44:55,763:INFO:Total runtime is 0.08847056229909261 minutes +2023-11-09 10:44:55,766:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:55,767:INFO:Initializing create_model() +2023-11-09 10:44:55,767:INFO:create_model(self=, estimator=et, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:55,767:INFO:Checking exceptions +2023-11-09 10:44:55,767:INFO:Importing libraries +2023-11-09 10:44:55,768:INFO:Copying training dataset +2023-11-09 10:44:55,771:INFO:Defining folds +2023-11-09 10:44:55,771:INFO:Declaring metric variables +2023-11-09 10:44:55,775:INFO:Importing untrained model +2023-11-09 10:44:55,778:INFO:Extra Trees Regressor Imported successfully +2023-11-09 10:44:55,784:INFO:Starting cross validation +2023-11-09 10:44:55,786:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:56,122:INFO:Calculating mean and std +2023-11-09 10:44:56,123:INFO:Creating metrics dataframe +2023-11-09 10:44:56,126:INFO:Uploading results into container +2023-11-09 10:44:56,128:INFO:Uploading model into container now +2023-11-09 10:44:56,129:INFO:_master_model_container: 14 +2023-11-09 10:44:56,129:INFO:_display_container: 2 +2023-11-09 10:44:56,130:INFO:ExtraTreesRegressor(n_jobs=-1, random_state=123) +2023-11-09 10:44:56,130:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:56,206:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:56,206:INFO:Creating metrics dataframe +2023-11-09 10:44:56,218:INFO:Initializing AdaBoost Regressor +2023-11-09 10:44:56,218:INFO:Total runtime is 0.09605745871861776 minutes +2023-11-09 10:44:56,222:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:56,222:INFO:Initializing create_model() +2023-11-09 10:44:56,222:INFO:create_model(self=, estimator=ada, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:56,222:INFO:Checking exceptions +2023-11-09 10:44:56,222:INFO:Importing libraries +2023-11-09 10:44:56,222:INFO:Copying training dataset +2023-11-09 10:44:56,226:INFO:Defining folds +2023-11-09 10:44:56,226:INFO:Declaring metric variables +2023-11-09 10:44:56,230:INFO:Importing untrained model +2023-11-09 10:44:56,233:INFO:AdaBoost Regressor Imported successfully +2023-11-09 10:44:56,239:INFO:Starting cross validation +2023-11-09 10:44:56,240:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:56,447:INFO:Calculating mean and std +2023-11-09 10:44:56,448:INFO:Creating metrics dataframe +2023-11-09 10:44:56,452:INFO:Uploading results into container +2023-11-09 10:44:56,453:INFO:Uploading model into container now +2023-11-09 10:44:56,453:INFO:_master_model_container: 15 +2023-11-09 10:44:56,454:INFO:_display_container: 2 +2023-11-09 10:44:56,454:INFO:AdaBoostRegressor(random_state=123) +2023-11-09 10:44:56,455:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:56,535:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:56,535:INFO:Creating metrics dataframe +2023-11-09 10:44:56,547:INFO:Initializing Gradient Boosting Regressor +2023-11-09 10:44:56,547:INFO:Total runtime is 0.10155067046483358 minutes +2023-11-09 10:44:56,551:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:56,552:INFO:Initializing create_model() +2023-11-09 10:44:56,552:INFO:create_model(self=, estimator=gbr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:56,552:INFO:Checking exceptions +2023-11-09 10:44:56,552:INFO:Importing libraries +2023-11-09 10:44:56,552:INFO:Copying training dataset +2023-11-09 10:44:56,557:INFO:Defining folds +2023-11-09 10:44:56,558:INFO:Declaring metric variables +2023-11-09 10:44:56,561:INFO:Importing untrained model +2023-11-09 10:44:56,565:INFO:Gradient Boosting Regressor Imported successfully +2023-11-09 10:44:56,572:INFO:Starting cross validation +2023-11-09 10:44:56,573:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:56,774:INFO:Calculating mean and std +2023-11-09 10:44:56,781:INFO:Creating metrics dataframe +2023-11-09 10:44:56,790:INFO:Uploading results into container +2023-11-09 10:44:56,791:INFO:Uploading model into container now +2023-11-09 10:44:56,791:INFO:_master_model_container: 16 +2023-11-09 10:44:56,791:INFO:_display_container: 2 +2023-11-09 10:44:56,792:INFO:GradientBoostingRegressor(random_state=123) +2023-11-09 10:44:56,792:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:56,900:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:56,900:INFO:Creating metrics dataframe +2023-11-09 10:44:56,910:INFO:Initializing Light Gradient Boosting Machine +2023-11-09 10:44:56,911:INFO:Total runtime is 0.10760351816813152 minutes +2023-11-09 10:44:56,918:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:56,918:INFO:Initializing create_model() +2023-11-09 10:44:56,918:INFO:create_model(self=, estimator=lightgbm, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:56,918:INFO:Checking exceptions +2023-11-09 10:44:56,918:INFO:Importing libraries +2023-11-09 10:44:56,918:INFO:Copying training dataset +2023-11-09 10:44:56,925:INFO:Defining folds +2023-11-09 10:44:56,925:INFO:Declaring metric variables +2023-11-09 10:44:56,929:INFO:Importing untrained model +2023-11-09 10:44:56,938:INFO:Light Gradient Boosting Machine Imported successfully +2023-11-09 10:44:56,950:INFO:Starting cross validation +2023-11-09 10:44:56,952:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:58,819:INFO:Calculating mean and std +2023-11-09 10:44:58,821:INFO:Creating metrics dataframe +2023-11-09 10:44:58,825:INFO:Uploading results into container +2023-11-09 10:44:58,827:INFO:Uploading model into container now +2023-11-09 10:44:58,828:INFO:_master_model_container: 17 +2023-11-09 10:44:58,828:INFO:_display_container: 2 +2023-11-09 10:44:58,828:INFO:LGBMRegressor(n_jobs=-1, random_state=123) +2023-11-09 10:44:58,829:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:58,907:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:58,907:INFO:Creating metrics dataframe +2023-11-09 10:44:58,924:INFO:Initializing Dummy Regressor +2023-11-09 10:44:58,924:INFO:Total runtime is 0.14116499821345013 minutes +2023-11-09 10:44:58,928:INFO:SubProcess create_model() called ================================== +2023-11-09 10:44:58,928:INFO:Initializing create_model() +2023-11-09 10:44:58,928:INFO:create_model(self=, estimator=dummy, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:58,928:INFO:Checking exceptions +2023-11-09 10:44:58,928:INFO:Importing libraries +2023-11-09 10:44:58,928:INFO:Copying training dataset +2023-11-09 10:44:58,932:INFO:Defining folds +2023-11-09 10:44:58,932:INFO:Declaring metric variables +2023-11-09 10:44:58,936:INFO:Importing untrained model +2023-11-09 10:44:58,939:INFO:Dummy Regressor Imported successfully +2023-11-09 10:44:58,945:INFO:Starting cross validation +2023-11-09 10:44:58,946:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 10:44:59,014:INFO:Calculating mean and std +2023-11-09 10:44:59,014:INFO:Creating metrics dataframe +2023-11-09 10:44:59,017:INFO:Uploading results into container +2023-11-09 10:44:59,018:INFO:Uploading model into container now +2023-11-09 10:44:59,018:INFO:_master_model_container: 18 +2023-11-09 10:44:59,018:INFO:_display_container: 2 +2023-11-09 10:44:59,019:INFO:DummyRegressor() +2023-11-09 10:44:59,019:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:59,096:INFO:SubProcess create_model() end ================================== +2023-11-09 10:44:59,096:INFO:Creating metrics dataframe +2023-11-09 10:44:59,117:INFO:Initializing create_model() +2023-11-09 10:44:59,118:INFO:create_model(self=, estimator=HuberRegressor(), fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=False, predict=False, fit_kwargs={}, groups=None, refit=True, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=None, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 10:44:59,118:INFO:Checking exceptions +2023-11-09 10:44:59,119:INFO:Importing libraries +2023-11-09 10:44:59,119:INFO:Copying training dataset +2023-11-09 10:44:59,122:INFO:Defining folds +2023-11-09 10:44:59,123:INFO:Declaring metric variables +2023-11-09 10:44:59,123:INFO:Importing untrained model +2023-11-09 10:44:59,123:INFO:Declaring custom model +2023-11-09 10:44:59,123:INFO:Huber Regressor Imported successfully +2023-11-09 10:44:59,124:INFO:Cross validation set to False +2023-11-09 10:44:59,124:INFO:Fitting Model +2023-11-09 10:44:59,147:INFO:HuberRegressor() +2023-11-09 10:44:59,147:INFO:create_model() successfully completed...................................... +2023-11-09 10:44:59,255:INFO:_master_model_container: 18 +2023-11-09 10:44:59,255:INFO:_display_container: 2 +2023-11-09 10:44:59,255:INFO:HuberRegressor() +2023-11-09 10:44:59,255:INFO:compare_models() successfully completed...................................... +2023-11-09 10:45:31,940:INFO:Initializing predict_model() +2023-11-09 10:45:31,943:INFO:predict_model(self=, estimator=HuberRegressor(), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=.encode_labels at 0x7fbb44aafd30>) +2023-11-09 10:45:31,944:INFO:Checking exceptions +2023-11-09 10:45:31,944:INFO:Preloading libraries +2023-11-09 10:45:31,961:INFO:Set up data. +2023-11-09 10:45:31,968:INFO:Set up index. +2023-11-09 11:09:16,097:INFO:PyCaret RegressionExperiment +2023-11-09 11:09:16,097:INFO:Logging name: reg-default-name +2023-11-09 11:09:16,097:INFO:ML Usecase: MLUsecase.REGRESSION +2023-11-09 11:09:16,097:INFO:version 3.1.0 +2023-11-09 11:09:16,097:INFO:Initializing setup() +2023-11-09 11:09:16,097:INFO:self.USI: de6d +2023-11-09 11:09:16,097:INFO:self._variable_keys: {'seed', 'idx', 'transform_target_param', 'gpu_param', 'target_param', 'log_plots_param', 'pipeline', 'logging_param', 'fold_groups_param', '_ml_usecase', 'html_param', 'gpu_n_jobs_param', 'y', 'y_test', 'y_train', 'memory', 'exp_id', 'X_test', 'exp_name_log', 'USI', 'data', 'X_train', 'fold_shuffle_param', 'X', 'fold_generator', 'n_jobs_param', '_available_plots'} +2023-11-09 11:09:16,097:INFO:Checking environment +2023-11-09 11:09:16,097:INFO:python_version: 3.8.18 +2023-11-09 11:09:16,097:INFO:python_build: ('default', 'Sep 11 2023 13:40:15') +2023-11-09 11:09:16,097:INFO:machine: x86_64 +2023-11-09 11:09:16,097:INFO:platform: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:09:16,098:INFO:Memory: svmem(total=8315187200, available=4920614912, percent=40.8, used=3059818496, free=319401984, active=1462353920, inactive=5675810816, buffers=339505152, cached=4596461568, shared=4476928, slab=650973184) +2023-11-09 11:09:16,098:INFO:Physical Core: 1 +2023-11-09 11:09:16,098:INFO:Logical Core: 2 +2023-11-09 11:09:16,098:INFO:Checking libraries +2023-11-09 11:09:16,098:INFO:System: +2023-11-09 11:09:16,098:INFO: python: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] +2023-11-09 11:09:16,098:INFO:executable: /workspaces/D2I-Jupyter-Notebook-Tools/.conda/bin/python +2023-11-09 11:09:16,098:INFO: machine: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:09:16,099:INFO:PyCaret required dependencies: +2023-11-09 11:09:16,099:INFO: pip: 23.3 +2023-11-09 11:09:16,099:INFO: setuptools: 68.0.0 +2023-11-09 11:09:16,099:INFO: pycaret: 3.1.0 +2023-11-09 11:09:16,099:INFO: IPython: 8.12.0 +2023-11-09 11:09:16,099:INFO: ipywidgets: 8.1.1 +2023-11-09 11:09:16,099:INFO: tqdm: 4.66.1 +2023-11-09 11:09:16,099:INFO: numpy: 1.23.5 +2023-11-09 11:09:16,099:INFO: pandas: 1.5.3 +2023-11-09 11:09:16,099:INFO: jinja2: 3.1.2 +2023-11-09 11:09:16,099:INFO: scipy: 1.10.1 +2023-11-09 11:09:16,099:INFO: joblib: 1.3.2 +2023-11-09 11:09:16,099:INFO: sklearn: 1.2.2 +2023-11-09 11:09:16,099:INFO: pyod: 1.1.1 +2023-11-09 11:09:16,099:INFO: imblearn: 0.11.0 +2023-11-09 11:09:16,100:INFO: category_encoders: 2.6.3 +2023-11-09 11:09:16,100:INFO: lightgbm: 4.1.0 +2023-11-09 11:09:16,100:INFO: numba: 0.58.1 +2023-11-09 11:09:16,100:INFO: requests: 2.31.0 +2023-11-09 11:09:16,100:INFO: matplotlib: 3.7.3 +2023-11-09 11:09:16,100:INFO: scikitplot: 0.3.7 +2023-11-09 11:09:16,100:INFO: yellowbrick: 1.5 +2023-11-09 11:09:16,100:INFO: plotly: 5.18.0 +2023-11-09 11:09:16,100:INFO: plotly-resampler: Not installed +2023-11-09 11:09:16,100:INFO: kaleido: 0.2.1 +2023-11-09 11:09:16,100:INFO: schemdraw: 0.15 +2023-11-09 11:09:16,100:INFO: statsmodels: 0.14.0 +2023-11-09 11:09:16,100:INFO: sktime: 0.21.1 +2023-11-09 11:09:16,100:INFO: tbats: 1.1.3 +2023-11-09 11:09:16,100:INFO: pmdarima: 2.0.4 +2023-11-09 11:09:16,100:INFO: psutil: 5.9.0 +2023-11-09 11:09:16,101:INFO: markupsafe: 2.1.3 +2023-11-09 11:09:16,101:INFO: pickle5: Not installed +2023-11-09 11:09:16,101:INFO: cloudpickle: 3.0.0 +2023-11-09 11:09:16,101:INFO: deprecation: 2.1.0 +2023-11-09 11:09:16,101:INFO: xxhash: 3.4.1 +2023-11-09 11:09:16,101:INFO: wurlitzer: 3.0.3 +2023-11-09 11:09:16,101:INFO:PyCaret optional dependencies: +2023-11-09 11:09:16,101:INFO: shap: Not installed +2023-11-09 11:09:16,101:INFO: interpret: Not installed +2023-11-09 11:09:16,101:INFO: umap: Not installed +2023-11-09 11:09:16,101:INFO: ydata_profiling: Not installed +2023-11-09 11:09:16,101:INFO: explainerdashboard: Not installed +2023-11-09 11:09:16,101:INFO: autoviz: Not installed +2023-11-09 11:09:16,101:INFO: fairlearn: Not installed +2023-11-09 11:09:16,101:INFO: deepchecks: Not installed +2023-11-09 11:09:16,101:INFO: xgboost: Not installed +2023-11-09 11:09:16,101:INFO: catboost: Not installed +2023-11-09 11:09:16,101:INFO: kmodes: Not installed +2023-11-09 11:09:16,101:INFO: mlxtend: Not installed +2023-11-09 11:09:16,102:INFO: statsforecast: Not installed +2023-11-09 11:09:16,102:INFO: tune_sklearn: Not installed +2023-11-09 11:09:16,102:INFO: ray: Not installed +2023-11-09 11:09:16,102:INFO: hyperopt: Not installed +2023-11-09 11:09:16,102:INFO: optuna: Not installed +2023-11-09 11:09:16,102:INFO: skopt: Not installed +2023-11-09 11:09:16,102:INFO: mlflow: Not installed +2023-11-09 11:09:16,102:INFO: gradio: Not installed +2023-11-09 11:09:16,102:INFO: fastapi: Not installed +2023-11-09 11:09:16,102:INFO: uvicorn: Not installed +2023-11-09 11:09:16,102:INFO: m2cgen: Not installed +2023-11-09 11:09:16,102:INFO: evidently: Not installed +2023-11-09 11:09:16,102:INFO: fugue: Not installed +2023-11-09 11:09:16,102:INFO: streamlit: Not installed +2023-11-09 11:09:16,102:INFO: prophet: Not installed +2023-11-09 11:09:16,102:INFO:None +2023-11-09 11:09:16,102:INFO:Set up data. +2023-11-09 11:09:16,106:INFO:Set up folding strategy. +2023-11-09 11:09:16,106:INFO:Set up train/test split. +2023-11-09 11:09:16,106:INFO:Set up data. +2023-11-09 11:09:16,109:INFO:Set up index. +2023-11-09 11:09:16,109:INFO:Assigning column types. +2023-11-09 11:09:16,112:INFO:Engine successfully changes for model 'lr' to 'sklearn'. +2023-11-09 11:09:16,112:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,116:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,121:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,206:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,253:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,254:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:16,254:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:16,255:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,259:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,263:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,312:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,350:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,351:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:16,351:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:16,351:INFO:Engine successfully changes for model 'lasso' to 'sklearn'. +2023-11-09 11:09:16,356:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,360:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,414:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,485:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,486:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:16,486:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:16,493:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,500:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,565:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,603:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,604:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:16,604:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:16,604:INFO:Engine successfully changes for model 'ridge' to 'sklearn'. +2023-11-09 11:09:16,612:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,661:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,700:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,700:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:16,701:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:16,709:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,758:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,814:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,815:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:16,815:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:16,815:INFO:Engine successfully changes for model 'en' to 'sklearn'. +2023-11-09 11:09:16,871:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,910:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:09:16,911:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:16,911:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:16,969:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:09:17,007:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:09:17,007:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:17,008:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:17,008:INFO:Engine successfully changes for model 'knn' to 'sklearn'. +2023-11-09 11:09:17,068:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:09:17,107:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:17,107:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:17,166:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:09:17,207:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:17,207:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:17,207:INFO:Engine successfully changes for model 'svm' to 'sklearn'. +2023-11-09 11:09:17,305:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:17,305:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:17,405:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:17,405:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:17,406:INFO:Preparing preprocessing pipeline... +2023-11-09 11:09:17,406:INFO:Set up target transformation. +2023-11-09 11:09:17,406:INFO:Set up simple imputation. +2023-11-09 11:09:17,407:INFO:Set up column name cleaning. +2023-11-09 11:09:17,433:INFO:Finished creating preprocessing pipeline. +2023-11-09 11:09:17,438:INFO:Pipeline: Pipeline(memory=FastMemory(location=/tmp/joblib), + steps=[('target_transformation', + TransformerWrapperWithInverse(transformer=TargetTransformer(estimator=PowerTransformer(standardize=False)))), + ('numerical_imputer', + TransformerWrapper(include=['Year', 'Series'], + transformer=SimpleImputer())), + ('categorical_imputer', + TransformerWrapper(include=[], + transformer=SimpleImputer(strategy='most_frequent'))), + ('clean_column_names', + TransformerWrapper(transformer=CleanColumnNames()))]) +2023-11-09 11:09:17,439:INFO:Creating final display dataframe. +2023-11-09 11:09:17,511:INFO:Setup _display_container: Description Value +0 Session id 123 +1 Target Average price All property types +2 Target type Regression +3 Original data shape (523, 4) +4 Transformed data shape (523, 4) +5 Transformed train set shape (372, 4) +6 Transformed test set shape (151, 4) +7 Numeric features 2 +8 Preprocess True +9 Imputation type simple +10 Numeric imputation mean +11 Categorical imputation mode +12 Transform target True +13 Transform target method yeo-johnson +14 Fold Generator TimeSeriesSplit +15 Fold Number 3 +16 CPU Jobs -1 +17 Use GPU False +18 Log Experiment False +19 Experiment Name reg-default-name +20 USI de6d +2023-11-09 11:09:17,639:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:17,639:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:17,819:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:17,819:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:09:17,820:INFO:setup() successfully completed in 1.72s............... +2023-11-09 11:09:17,891:INFO:Initializing compare_models() +2023-11-09 11:09:17,892:INFO:compare_models(self=, include=None, fold=None, round=4, cross_validation=True, sort=MAE, n_select=1, budget_time=None, turbo=True, errors=ignore, fit_kwargs=None, groups=None, experiment_custom_tags=None, probability_threshold=None, verbose=True, parallel=None, caller_params={'self': , 'include': None, 'exclude': None, 'fold': None, 'round': 4, 'cross_validation': True, 'sort': 'MAE', 'n_select': 1, 'budget_time': None, 'turbo': True, 'errors': 'ignore', 'fit_kwargs': None, 'groups': None, 'experiment_custom_tags': None, 'engine': None, 'verbose': True, 'parallel': None, '__class__': }, exclude=None) +2023-11-09 11:09:17,892:INFO:Checking exceptions +2023-11-09 11:09:17,894:INFO:Preparing display monitor +2023-11-09 11:09:17,919:INFO:Initializing Linear Regression +2023-11-09 11:09:17,920:INFO:Total runtime is 1.1650721232096354e-05 minutes +2023-11-09 11:09:17,923:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:17,923:INFO:Initializing create_model() +2023-11-09 11:09:17,923:INFO:create_model(self=, estimator=lr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:17,923:INFO:Checking exceptions +2023-11-09 11:09:17,924:INFO:Importing libraries +2023-11-09 11:09:17,924:INFO:Copying training dataset +2023-11-09 11:09:17,927:INFO:Defining folds +2023-11-09 11:09:17,927:INFO:Declaring metric variables +2023-11-09 11:09:17,930:INFO:Importing untrained model +2023-11-09 11:09:17,934:INFO:Linear Regression Imported successfully +2023-11-09 11:09:17,941:INFO:Starting cross validation +2023-11-09 11:09:17,942:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:19,796:INFO:Calculating mean and std +2023-11-09 11:09:19,798:INFO:Creating metrics dataframe +2023-11-09 11:09:19,804:INFO:Uploading results into container +2023-11-09 11:09:19,805:INFO:Uploading model into container now +2023-11-09 11:09:19,805:INFO:_master_model_container: 1 +2023-11-09 11:09:19,806:INFO:_display_container: 2 +2023-11-09 11:09:19,806:INFO:LinearRegression(n_jobs=-1) +2023-11-09 11:09:19,806:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:19,972:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:19,973:INFO:Creating metrics dataframe +2023-11-09 11:09:19,988:INFO:Initializing Lasso Regression +2023-11-09 11:09:19,989:INFO:Total runtime is 0.03448711236317953 minutes +2023-11-09 11:09:19,992:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:19,993:INFO:Initializing create_model() +2023-11-09 11:09:19,993:INFO:create_model(self=, estimator=lasso, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:19,993:INFO:Checking exceptions +2023-11-09 11:09:19,993:INFO:Importing libraries +2023-11-09 11:09:19,993:INFO:Copying training dataset +2023-11-09 11:09:19,996:INFO:Defining folds +2023-11-09 11:09:19,997:INFO:Declaring metric variables +2023-11-09 11:09:20,002:INFO:Importing untrained model +2023-11-09 11:09:20,007:INFO:Lasso Regression Imported successfully +2023-11-09 11:09:20,015:INFO:Starting cross validation +2023-11-09 11:09:20,016:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:20,129:INFO:Calculating mean and std +2023-11-09 11:09:20,130:INFO:Creating metrics dataframe +2023-11-09 11:09:20,135:INFO:Uploading results into container +2023-11-09 11:09:20,136:INFO:Uploading model into container now +2023-11-09 11:09:20,136:INFO:_master_model_container: 2 +2023-11-09 11:09:20,136:INFO:_display_container: 2 +2023-11-09 11:09:20,137:INFO:Lasso(random_state=123) +2023-11-09 11:09:20,137:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:20,301:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:20,301:INFO:Creating metrics dataframe +2023-11-09 11:09:20,309:INFO:Initializing Ridge Regression +2023-11-09 11:09:20,309:INFO:Total runtime is 0.039824056625366214 minutes +2023-11-09 11:09:20,312:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:20,313:INFO:Initializing create_model() +2023-11-09 11:09:20,313:INFO:create_model(self=, estimator=ridge, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:20,313:INFO:Checking exceptions +2023-11-09 11:09:20,313:INFO:Importing libraries +2023-11-09 11:09:20,313:INFO:Copying training dataset +2023-11-09 11:09:20,317:INFO:Defining folds +2023-11-09 11:09:20,317:INFO:Declaring metric variables +2023-11-09 11:09:20,321:INFO:Importing untrained model +2023-11-09 11:09:20,324:INFO:Ridge Regression Imported successfully +2023-11-09 11:09:20,330:INFO:Starting cross validation +2023-11-09 11:09:20,331:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:20,400:INFO:Calculating mean and std +2023-11-09 11:09:20,402:INFO:Creating metrics dataframe +2023-11-09 11:09:20,404:INFO:Uploading results into container +2023-11-09 11:09:20,405:INFO:Uploading model into container now +2023-11-09 11:09:20,405:INFO:_master_model_container: 3 +2023-11-09 11:09:20,405:INFO:_display_container: 2 +2023-11-09 11:09:20,406:INFO:Ridge(random_state=123) +2023-11-09 11:09:20,406:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:20,535:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:20,535:INFO:Creating metrics dataframe +2023-11-09 11:09:20,544:INFO:Initializing Elastic Net +2023-11-09 11:09:20,544:INFO:Total runtime is 0.04374899466832479 minutes +2023-11-09 11:09:20,548:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:20,548:INFO:Initializing create_model() +2023-11-09 11:09:20,548:INFO:create_model(self=, estimator=en, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:20,548:INFO:Checking exceptions +2023-11-09 11:09:20,548:INFO:Importing libraries +2023-11-09 11:09:20,549:INFO:Copying training dataset +2023-11-09 11:09:20,552:INFO:Defining folds +2023-11-09 11:09:20,552:INFO:Declaring metric variables +2023-11-09 11:09:20,556:INFO:Importing untrained model +2023-11-09 11:09:20,560:INFO:Elastic Net Imported successfully +2023-11-09 11:09:20,565:INFO:Starting cross validation +2023-11-09 11:09:20,567:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:20,712:INFO:Calculating mean and std +2023-11-09 11:09:20,713:INFO:Creating metrics dataframe +2023-11-09 11:09:20,717:INFO:Uploading results into container +2023-11-09 11:09:20,718:INFO:Uploading model into container now +2023-11-09 11:09:20,718:INFO:_master_model_container: 4 +2023-11-09 11:09:20,718:INFO:_display_container: 2 +2023-11-09 11:09:20,719:INFO:ElasticNet(random_state=123) +2023-11-09 11:09:20,719:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:20,889:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:20,889:INFO:Creating metrics dataframe +2023-11-09 11:09:20,898:INFO:Initializing Least Angle Regression +2023-11-09 11:09:20,898:INFO:Total runtime is 0.04964574972788493 minutes +2023-11-09 11:09:20,903:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:20,903:INFO:Initializing create_model() +2023-11-09 11:09:20,903:INFO:create_model(self=, estimator=lar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:20,903:INFO:Checking exceptions +2023-11-09 11:09:20,903:INFO:Importing libraries +2023-11-09 11:09:20,903:INFO:Copying training dataset +2023-11-09 11:09:20,907:INFO:Defining folds +2023-11-09 11:09:20,907:INFO:Declaring metric variables +2023-11-09 11:09:20,912:INFO:Importing untrained model +2023-11-09 11:09:20,915:INFO:Least Angle Regression Imported successfully +2023-11-09 11:09:20,921:INFO:Starting cross validation +2023-11-09 11:09:20,922:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:21,003:INFO:Calculating mean and std +2023-11-09 11:09:21,003:INFO:Creating metrics dataframe +2023-11-09 11:09:21,007:INFO:Uploading results into container +2023-11-09 11:09:21,008:INFO:Uploading model into container now +2023-11-09 11:09:21,009:INFO:_master_model_container: 5 +2023-11-09 11:09:21,009:INFO:_display_container: 2 +2023-11-09 11:09:21,009:INFO:Lars(random_state=123) +2023-11-09 11:09:21,010:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:21,145:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:21,145:INFO:Creating metrics dataframe +2023-11-09 11:09:21,154:INFO:Initializing Lasso Least Angle Regression +2023-11-09 11:09:21,154:INFO:Total runtime is 0.05390775998433431 minutes +2023-11-09 11:09:21,157:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:21,158:INFO:Initializing create_model() +2023-11-09 11:09:21,158:INFO:create_model(self=, estimator=llar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:21,158:INFO:Checking exceptions +2023-11-09 11:09:21,158:INFO:Importing libraries +2023-11-09 11:09:21,158:INFO:Copying training dataset +2023-11-09 11:09:21,162:INFO:Defining folds +2023-11-09 11:09:21,162:INFO:Declaring metric variables +2023-11-09 11:09:21,165:INFO:Importing untrained model +2023-11-09 11:09:21,168:INFO:Lasso Least Angle Regression Imported successfully +2023-11-09 11:09:21,176:INFO:Starting cross validation +2023-11-09 11:09:21,178:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:21,263:INFO:Calculating mean and std +2023-11-09 11:09:21,264:INFO:Creating metrics dataframe +2023-11-09 11:09:21,267:INFO:Uploading results into container +2023-11-09 11:09:21,268:INFO:Uploading model into container now +2023-11-09 11:09:21,268:INFO:_master_model_container: 6 +2023-11-09 11:09:21,268:INFO:_display_container: 2 +2023-11-09 11:09:21,268:INFO:LassoLars(random_state=123) +2023-11-09 11:09:21,268:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:21,401:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:21,401:INFO:Creating metrics dataframe +2023-11-09 11:09:21,410:INFO:Initializing Orthogonal Matching Pursuit +2023-11-09 11:09:21,411:INFO:Total runtime is 0.058187222480773924 minutes +2023-11-09 11:09:21,414:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:21,415:INFO:Initializing create_model() +2023-11-09 11:09:21,415:INFO:create_model(self=, estimator=omp, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:21,415:INFO:Checking exceptions +2023-11-09 11:09:21,415:INFO:Importing libraries +2023-11-09 11:09:21,415:INFO:Copying training dataset +2023-11-09 11:09:21,419:INFO:Defining folds +2023-11-09 11:09:21,419:INFO:Declaring metric variables +2023-11-09 11:09:21,423:INFO:Importing untrained model +2023-11-09 11:09:21,426:INFO:Orthogonal Matching Pursuit Imported successfully +2023-11-09 11:09:21,432:INFO:Starting cross validation +2023-11-09 11:09:21,433:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:21,513:INFO:Calculating mean and std +2023-11-09 11:09:21,514:INFO:Creating metrics dataframe +2023-11-09 11:09:21,517:INFO:Uploading results into container +2023-11-09 11:09:21,518:INFO:Uploading model into container now +2023-11-09 11:09:21,518:INFO:_master_model_container: 7 +2023-11-09 11:09:21,519:INFO:_display_container: 2 +2023-11-09 11:09:21,519:INFO:OrthogonalMatchingPursuit() +2023-11-09 11:09:21,519:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:21,673:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:21,673:INFO:Creating metrics dataframe +2023-11-09 11:09:21,683:INFO:Initializing Bayesian Ridge +2023-11-09 11:09:21,683:INFO:Total runtime is 0.0627333402633667 minutes +2023-11-09 11:09:21,687:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:21,688:INFO:Initializing create_model() +2023-11-09 11:09:21,688:INFO:create_model(self=, estimator=br, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:21,688:INFO:Checking exceptions +2023-11-09 11:09:21,688:INFO:Importing libraries +2023-11-09 11:09:21,688:INFO:Copying training dataset +2023-11-09 11:09:21,693:INFO:Defining folds +2023-11-09 11:09:21,693:INFO:Declaring metric variables +2023-11-09 11:09:21,698:INFO:Importing untrained model +2023-11-09 11:09:21,701:INFO:Bayesian Ridge Imported successfully +2023-11-09 11:09:21,707:INFO:Starting cross validation +2023-11-09 11:09:21,708:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:21,787:INFO:Calculating mean and std +2023-11-09 11:09:21,788:INFO:Creating metrics dataframe +2023-11-09 11:09:21,791:INFO:Uploading results into container +2023-11-09 11:09:21,792:INFO:Uploading model into container now +2023-11-09 11:09:21,792:INFO:_master_model_container: 8 +2023-11-09 11:09:21,793:INFO:_display_container: 2 +2023-11-09 11:09:21,793:INFO:BayesianRidge() +2023-11-09 11:09:21,793:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:21,937:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:21,938:INFO:Creating metrics dataframe +2023-11-09 11:09:21,947:INFO:Initializing Passive Aggressive Regressor +2023-11-09 11:09:21,947:INFO:Total runtime is 0.06713413000106812 minutes +2023-11-09 11:09:21,951:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:21,952:INFO:Initializing create_model() +2023-11-09 11:09:21,952:INFO:create_model(self=, estimator=par, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:21,952:INFO:Checking exceptions +2023-11-09 11:09:21,952:INFO:Importing libraries +2023-11-09 11:09:21,953:INFO:Copying training dataset +2023-11-09 11:09:21,957:INFO:Defining folds +2023-11-09 11:09:21,957:INFO:Declaring metric variables +2023-11-09 11:09:21,961:INFO:Importing untrained model +2023-11-09 11:09:21,964:INFO:Passive Aggressive Regressor Imported successfully +2023-11-09 11:09:21,970:INFO:Starting cross validation +2023-11-09 11:09:21,972:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:22,062:INFO:Calculating mean and std +2023-11-09 11:09:22,063:INFO:Creating metrics dataframe +2023-11-09 11:09:22,066:INFO:Uploading results into container +2023-11-09 11:09:22,068:INFO:Uploading model into container now +2023-11-09 11:09:22,068:INFO:_master_model_container: 9 +2023-11-09 11:09:22,068:INFO:_display_container: 2 +2023-11-09 11:09:22,069:INFO:PassiveAggressiveRegressor(random_state=123) +2023-11-09 11:09:22,069:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:22,215:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:22,215:INFO:Creating metrics dataframe +2023-11-09 11:09:22,225:INFO:Initializing Huber Regressor +2023-11-09 11:09:22,225:INFO:Total runtime is 0.07176302671432495 minutes +2023-11-09 11:09:22,229:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:22,230:INFO:Initializing create_model() +2023-11-09 11:09:22,230:INFO:create_model(self=, estimator=huber, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:22,230:INFO:Checking exceptions +2023-11-09 11:09:22,230:INFO:Importing libraries +2023-11-09 11:09:22,230:INFO:Copying training dataset +2023-11-09 11:09:22,234:INFO:Defining folds +2023-11-09 11:09:22,234:INFO:Declaring metric variables +2023-11-09 11:09:22,237:INFO:Importing untrained model +2023-11-09 11:09:22,241:INFO:Huber Regressor Imported successfully +2023-11-09 11:09:22,247:INFO:Starting cross validation +2023-11-09 11:09:22,248:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:22,365:INFO:Calculating mean and std +2023-11-09 11:09:22,367:INFO:Creating metrics dataframe +2023-11-09 11:09:22,370:INFO:Uploading results into container +2023-11-09 11:09:22,372:INFO:Uploading model into container now +2023-11-09 11:09:22,372:INFO:_master_model_container: 10 +2023-11-09 11:09:22,372:INFO:_display_container: 2 +2023-11-09 11:09:22,373:INFO:HuberRegressor() +2023-11-09 11:09:22,373:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:22,515:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:22,515:INFO:Creating metrics dataframe +2023-11-09 11:09:22,525:INFO:Initializing K Neighbors Regressor +2023-11-09 11:09:22,526:INFO:Total runtime is 0.07676899830500285 minutes +2023-11-09 11:09:22,529:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:22,530:INFO:Initializing create_model() +2023-11-09 11:09:22,530:INFO:create_model(self=, estimator=knn, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:22,530:INFO:Checking exceptions +2023-11-09 11:09:22,530:INFO:Importing libraries +2023-11-09 11:09:22,530:INFO:Copying training dataset +2023-11-09 11:09:22,535:INFO:Defining folds +2023-11-09 11:09:22,535:INFO:Declaring metric variables +2023-11-09 11:09:22,539:INFO:Importing untrained model +2023-11-09 11:09:22,543:INFO:K Neighbors Regressor Imported successfully +2023-11-09 11:09:22,548:INFO:Starting cross validation +2023-11-09 11:09:22,549:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:22,652:INFO:Calculating mean and std +2023-11-09 11:09:22,653:INFO:Creating metrics dataframe +2023-11-09 11:09:22,657:INFO:Uploading results into container +2023-11-09 11:09:22,658:INFO:Uploading model into container now +2023-11-09 11:09:22,658:INFO:_master_model_container: 11 +2023-11-09 11:09:22,658:INFO:_display_container: 2 +2023-11-09 11:09:22,659:INFO:KNeighborsRegressor(n_jobs=-1) +2023-11-09 11:09:22,659:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:22,808:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:22,809:INFO:Creating metrics dataframe +2023-11-09 11:09:22,824:INFO:Initializing Decision Tree Regressor +2023-11-09 11:09:22,824:INFO:Total runtime is 0.0817442536354065 minutes +2023-11-09 11:09:22,828:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:22,829:INFO:Initializing create_model() +2023-11-09 11:09:22,829:INFO:create_model(self=, estimator=dt, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:22,829:INFO:Checking exceptions +2023-11-09 11:09:22,829:INFO:Importing libraries +2023-11-09 11:09:22,829:INFO:Copying training dataset +2023-11-09 11:09:22,835:INFO:Defining folds +2023-11-09 11:09:22,835:INFO:Declaring metric variables +2023-11-09 11:09:22,838:INFO:Importing untrained model +2023-11-09 11:09:22,843:INFO:Decision Tree Regressor Imported successfully +2023-11-09 11:09:22,851:INFO:Starting cross validation +2023-11-09 11:09:22,852:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:23,020:INFO:Calculating mean and std +2023-11-09 11:09:23,022:INFO:Creating metrics dataframe +2023-11-09 11:09:23,038:INFO:Uploading results into container +2023-11-09 11:09:23,043:INFO:Uploading model into container now +2023-11-09 11:09:23,044:INFO:_master_model_container: 12 +2023-11-09 11:09:23,044:INFO:_display_container: 2 +2023-11-09 11:09:23,045:INFO:DecisionTreeRegressor(random_state=123) +2023-11-09 11:09:23,045:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:23,283:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:23,283:INFO:Creating metrics dataframe +2023-11-09 11:09:23,304:INFO:Initializing Random Forest Regressor +2023-11-09 11:09:23,304:INFO:Total runtime is 0.08975063959757487 minutes +2023-11-09 11:09:23,308:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:23,309:INFO:Initializing create_model() +2023-11-09 11:09:23,309:INFO:create_model(self=, estimator=rf, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:23,309:INFO:Checking exceptions +2023-11-09 11:09:23,309:INFO:Importing libraries +2023-11-09 11:09:23,309:INFO:Copying training dataset +2023-11-09 11:09:23,314:INFO:Defining folds +2023-11-09 11:09:23,314:INFO:Declaring metric variables +2023-11-09 11:09:23,318:INFO:Importing untrained model +2023-11-09 11:09:23,322:INFO:Random Forest Regressor Imported successfully +2023-11-09 11:09:23,329:INFO:Starting cross validation +2023-11-09 11:09:23,330:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:23,756:INFO:Calculating mean and std +2023-11-09 11:09:23,757:INFO:Creating metrics dataframe +2023-11-09 11:09:23,761:INFO:Uploading results into container +2023-11-09 11:09:23,762:INFO:Uploading model into container now +2023-11-09 11:09:23,762:INFO:_master_model_container: 13 +2023-11-09 11:09:23,762:INFO:_display_container: 2 +2023-11-09 11:09:23,763:INFO:RandomForestRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:09:23,763:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:23,897:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:23,897:INFO:Creating metrics dataframe +2023-11-09 11:09:23,907:INFO:Initializing Extra Trees Regressor +2023-11-09 11:09:23,908:INFO:Total runtime is 0.09980345964431762 minutes +2023-11-09 11:09:23,911:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:23,912:INFO:Initializing create_model() +2023-11-09 11:09:23,912:INFO:create_model(self=, estimator=et, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:23,912:INFO:Checking exceptions +2023-11-09 11:09:23,912:INFO:Importing libraries +2023-11-09 11:09:23,912:INFO:Copying training dataset +2023-11-09 11:09:23,916:INFO:Defining folds +2023-11-09 11:09:23,916:INFO:Declaring metric variables +2023-11-09 11:09:23,920:INFO:Importing untrained model +2023-11-09 11:09:23,923:INFO:Extra Trees Regressor Imported successfully +2023-11-09 11:09:23,930:INFO:Starting cross validation +2023-11-09 11:09:23,931:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:24,292:INFO:Calculating mean and std +2023-11-09 11:09:24,293:INFO:Creating metrics dataframe +2023-11-09 11:09:24,297:INFO:Uploading results into container +2023-11-09 11:09:24,297:INFO:Uploading model into container now +2023-11-09 11:09:24,298:INFO:_master_model_container: 14 +2023-11-09 11:09:24,298:INFO:_display_container: 2 +2023-11-09 11:09:24,298:INFO:ExtraTreesRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:09:24,298:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:24,432:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:24,432:INFO:Creating metrics dataframe +2023-11-09 11:09:24,442:INFO:Initializing AdaBoost Regressor +2023-11-09 11:09:24,442:INFO:Total runtime is 0.10870830217997232 minutes +2023-11-09 11:09:24,447:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:24,448:INFO:Initializing create_model() +2023-11-09 11:09:24,448:INFO:create_model(self=, estimator=ada, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:24,448:INFO:Checking exceptions +2023-11-09 11:09:24,448:INFO:Importing libraries +2023-11-09 11:09:24,448:INFO:Copying training dataset +2023-11-09 11:09:24,451:INFO:Defining folds +2023-11-09 11:09:24,452:INFO:Declaring metric variables +2023-11-09 11:09:24,455:INFO:Importing untrained model +2023-11-09 11:09:24,458:INFO:AdaBoost Regressor Imported successfully +2023-11-09 11:09:24,464:INFO:Starting cross validation +2023-11-09 11:09:24,465:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:24,664:INFO:Calculating mean and std +2023-11-09 11:09:24,665:INFO:Creating metrics dataframe +2023-11-09 11:09:24,668:INFO:Uploading results into container +2023-11-09 11:09:24,669:INFO:Uploading model into container now +2023-11-09 11:09:24,669:INFO:_master_model_container: 15 +2023-11-09 11:09:24,669:INFO:_display_container: 2 +2023-11-09 11:09:24,670:INFO:AdaBoostRegressor(random_state=123) +2023-11-09 11:09:24,670:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:24,796:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:24,796:INFO:Creating metrics dataframe +2023-11-09 11:09:24,808:INFO:Initializing Gradient Boosting Regressor +2023-11-09 11:09:24,809:INFO:Total runtime is 0.11481863657633462 minutes +2023-11-09 11:09:24,812:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:24,812:INFO:Initializing create_model() +2023-11-09 11:09:24,813:INFO:create_model(self=, estimator=gbr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:24,813:INFO:Checking exceptions +2023-11-09 11:09:24,813:INFO:Importing libraries +2023-11-09 11:09:24,813:INFO:Copying training dataset +2023-11-09 11:09:24,817:INFO:Defining folds +2023-11-09 11:09:24,817:INFO:Declaring metric variables +2023-11-09 11:09:24,821:INFO:Importing untrained model +2023-11-09 11:09:24,824:INFO:Gradient Boosting Regressor Imported successfully +2023-11-09 11:09:24,830:INFO:Starting cross validation +2023-11-09 11:09:24,832:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:24,996:INFO:Calculating mean and std +2023-11-09 11:09:24,997:INFO:Creating metrics dataframe +2023-11-09 11:09:25,001:INFO:Uploading results into container +2023-11-09 11:09:25,002:INFO:Uploading model into container now +2023-11-09 11:09:25,002:INFO:_master_model_container: 16 +2023-11-09 11:09:25,003:INFO:_display_container: 2 +2023-11-09 11:09:25,003:INFO:GradientBoostingRegressor(random_state=123) +2023-11-09 11:09:25,003:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:25,149:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:25,149:INFO:Creating metrics dataframe +2023-11-09 11:09:25,164:INFO:Initializing Light Gradient Boosting Machine +2023-11-09 11:09:25,165:INFO:Total runtime is 0.1207538604736328 minutes +2023-11-09 11:09:25,168:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:25,169:INFO:Initializing create_model() +2023-11-09 11:09:25,169:INFO:create_model(self=, estimator=lightgbm, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:25,169:INFO:Checking exceptions +2023-11-09 11:09:25,169:INFO:Importing libraries +2023-11-09 11:09:25,169:INFO:Copying training dataset +2023-11-09 11:09:25,174:INFO:Defining folds +2023-11-09 11:09:25,174:INFO:Declaring metric variables +2023-11-09 11:09:25,177:INFO:Importing untrained model +2023-11-09 11:09:25,182:INFO:Light Gradient Boosting Machine Imported successfully +2023-11-09 11:09:25,190:INFO:Starting cross validation +2023-11-09 11:09:25,192:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:25,460:INFO:Calculating mean and std +2023-11-09 11:09:25,462:INFO:Creating metrics dataframe +2023-11-09 11:09:25,465:INFO:Uploading results into container +2023-11-09 11:09:25,466:INFO:Uploading model into container now +2023-11-09 11:09:25,466:INFO:_master_model_container: 17 +2023-11-09 11:09:25,466:INFO:_display_container: 2 +2023-11-09 11:09:25,467:INFO:LGBMRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:09:25,467:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:25,615:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:25,615:INFO:Creating metrics dataframe +2023-11-09 11:09:25,626:INFO:Initializing Dummy Regressor +2023-11-09 11:09:25,626:INFO:Total runtime is 0.12844714323679604 minutes +2023-11-09 11:09:25,631:INFO:SubProcess create_model() called ================================== +2023-11-09 11:09:25,631:INFO:Initializing create_model() +2023-11-09 11:09:25,631:INFO:create_model(self=, estimator=dummy, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:25,631:INFO:Checking exceptions +2023-11-09 11:09:25,631:INFO:Importing libraries +2023-11-09 11:09:25,631:INFO:Copying training dataset +2023-11-09 11:09:25,635:INFO:Defining folds +2023-11-09 11:09:25,636:INFO:Declaring metric variables +2023-11-09 11:09:25,640:INFO:Importing untrained model +2023-11-09 11:09:25,643:INFO:Dummy Regressor Imported successfully +2023-11-09 11:09:25,650:INFO:Starting cross validation +2023-11-09 11:09:25,651:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:09:25,725:INFO:Calculating mean and std +2023-11-09 11:09:25,726:INFO:Creating metrics dataframe +2023-11-09 11:09:25,729:INFO:Uploading results into container +2023-11-09 11:09:25,729:INFO:Uploading model into container now +2023-11-09 11:09:25,729:INFO:_master_model_container: 18 +2023-11-09 11:09:25,730:INFO:_display_container: 2 +2023-11-09 11:09:25,730:INFO:DummyRegressor() +2023-11-09 11:09:25,730:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:25,886:INFO:SubProcess create_model() end ================================== +2023-11-09 11:09:25,886:INFO:Creating metrics dataframe +2023-11-09 11:09:25,908:INFO:Initializing create_model() +2023-11-09 11:09:25,908:INFO:create_model(self=, estimator=HuberRegressor(), fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=False, predict=False, fit_kwargs={}, groups=None, refit=True, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=None, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:09:25,908:INFO:Checking exceptions +2023-11-09 11:09:25,910:INFO:Importing libraries +2023-11-09 11:09:25,910:INFO:Copying training dataset +2023-11-09 11:09:25,913:INFO:Defining folds +2023-11-09 11:09:25,914:INFO:Declaring metric variables +2023-11-09 11:09:25,914:INFO:Importing untrained model +2023-11-09 11:09:25,914:INFO:Declaring custom model +2023-11-09 11:09:25,914:INFO:Huber Regressor Imported successfully +2023-11-09 11:09:25,915:INFO:Cross validation set to False +2023-11-09 11:09:25,915:INFO:Fitting Model +2023-11-09 11:09:25,939:INFO:HuberRegressor() +2023-11-09 11:09:25,939:INFO:create_model() successfully completed...................................... +2023-11-09 11:09:26,110:INFO:_master_model_container: 18 +2023-11-09 11:09:26,111:INFO:_display_container: 2 +2023-11-09 11:09:26,111:INFO:HuberRegressor() +2023-11-09 11:09:26,111:INFO:compare_models() successfully completed...................................... +2023-11-09 11:09:26,275:INFO:Initializing predict_model() +2023-11-09 11:09:26,275:INFO:predict_model(self=, estimator=HuberRegressor(), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=.encode_labels at 0x7fbb2ca7a550>) +2023-11-09 11:09:26,276:INFO:Checking exceptions +2023-11-09 11:09:26,276:INFO:Preloading libraries +2023-11-09 11:09:26,278:INFO:Set up data. +2023-11-09 11:09:26,281:INFO:Set up index. +2023-11-09 11:12:06,931:WARNING:/tmp/ipykernel_54540/3774887149.py:1: SettingWithCopyWarning: + + +A value is trying to be set on a copy of a slice from a DataFrame + +See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy + + +2023-11-09 11:12:14,496:WARNING:/tmp/ipykernel_54540/2181003279.py:1: SettingWithCopyWarning: + + +A value is trying to be set on a copy of a slice from a DataFrame + +See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy + + +2023-11-09 11:13:58,323:INFO:PyCaret RegressionExperiment +2023-11-09 11:13:58,324:INFO:Logging name: reg-default-name +2023-11-09 11:13:58,324:INFO:ML Usecase: MLUsecase.REGRESSION +2023-11-09 11:13:58,324:INFO:version 3.1.0 +2023-11-09 11:13:58,324:INFO:Initializing setup() +2023-11-09 11:13:58,324:INFO:self.USI: a563 +2023-11-09 11:13:58,325:INFO:self._variable_keys: {'seed', 'idx', 'transform_target_param', 'gpu_param', 'target_param', 'log_plots_param', 'pipeline', 'logging_param', 'fold_groups_param', '_ml_usecase', 'html_param', 'gpu_n_jobs_param', 'y', 'y_test', 'y_train', 'memory', 'exp_id', 'X_test', 'exp_name_log', 'USI', 'data', 'X_train', 'fold_shuffle_param', 'X', 'fold_generator', 'n_jobs_param', '_available_plots'} +2023-11-09 11:13:58,325:INFO:Checking environment +2023-11-09 11:13:58,325:INFO:python_version: 3.8.18 +2023-11-09 11:13:58,325:INFO:python_build: ('default', 'Sep 11 2023 13:40:15') +2023-11-09 11:13:58,325:INFO:machine: x86_64 +2023-11-09 11:13:58,325:INFO:platform: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:13:58,326:INFO:Memory: svmem(total=8315187200, available=4599803904, percent=44.7, used=3380736000, free=272965632, active=1468928000, inactive=5733826560, buffers=333897728, cached=4327587840, shared=4489216, slab=651264000) +2023-11-09 11:13:58,326:INFO:Physical Core: 1 +2023-11-09 11:13:58,326:INFO:Logical Core: 2 +2023-11-09 11:13:58,326:INFO:Checking libraries +2023-11-09 11:13:58,326:INFO:System: +2023-11-09 11:13:58,326:INFO: python: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] +2023-11-09 11:13:58,326:INFO:executable: /workspaces/D2I-Jupyter-Notebook-Tools/.conda/bin/python +2023-11-09 11:13:58,326:INFO: machine: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:13:58,326:INFO:PyCaret required dependencies: +2023-11-09 11:13:58,326:INFO: pip: 23.3 +2023-11-09 11:13:58,326:INFO: setuptools: 68.0.0 +2023-11-09 11:13:58,326:INFO: pycaret: 3.1.0 +2023-11-09 11:13:58,327:INFO: IPython: 8.12.0 +2023-11-09 11:13:58,327:INFO: ipywidgets: 8.1.1 +2023-11-09 11:13:58,327:INFO: tqdm: 4.66.1 +2023-11-09 11:13:58,327:INFO: numpy: 1.23.5 +2023-11-09 11:13:58,327:INFO: pandas: 1.5.3 +2023-11-09 11:13:58,327:INFO: jinja2: 3.1.2 +2023-11-09 11:13:58,327:INFO: scipy: 1.10.1 +2023-11-09 11:13:58,327:INFO: joblib: 1.3.2 +2023-11-09 11:13:58,327:INFO: sklearn: 1.2.2 +2023-11-09 11:13:58,327:INFO: pyod: 1.1.1 +2023-11-09 11:13:58,327:INFO: imblearn: 0.11.0 +2023-11-09 11:13:58,327:INFO: category_encoders: 2.6.3 +2023-11-09 11:13:58,327:INFO: lightgbm: 4.1.0 +2023-11-09 11:13:58,327:INFO: numba: 0.58.1 +2023-11-09 11:13:58,327:INFO: requests: 2.31.0 +2023-11-09 11:13:58,327:INFO: matplotlib: 3.7.3 +2023-11-09 11:13:58,327:INFO: scikitplot: 0.3.7 +2023-11-09 11:13:58,327:INFO: yellowbrick: 1.5 +2023-11-09 11:13:58,327:INFO: plotly: 5.18.0 +2023-11-09 11:13:58,328:INFO: plotly-resampler: Not installed +2023-11-09 11:13:58,328:INFO: kaleido: 0.2.1 +2023-11-09 11:13:58,328:INFO: schemdraw: 0.15 +2023-11-09 11:13:58,328:INFO: statsmodels: 0.14.0 +2023-11-09 11:13:58,328:INFO: sktime: 0.21.1 +2023-11-09 11:13:58,328:INFO: tbats: 1.1.3 +2023-11-09 11:13:58,328:INFO: pmdarima: 2.0.4 +2023-11-09 11:13:58,328:INFO: psutil: 5.9.0 +2023-11-09 11:13:58,328:INFO: markupsafe: 2.1.3 +2023-11-09 11:13:58,328:INFO: pickle5: Not installed +2023-11-09 11:13:58,328:INFO: cloudpickle: 3.0.0 +2023-11-09 11:13:58,328:INFO: deprecation: 2.1.0 +2023-11-09 11:13:58,328:INFO: xxhash: 3.4.1 +2023-11-09 11:13:58,328:INFO: wurlitzer: 3.0.3 +2023-11-09 11:13:58,328:INFO:PyCaret optional dependencies: +2023-11-09 11:13:58,328:INFO: shap: Not installed +2023-11-09 11:13:58,328:INFO: interpret: Not installed +2023-11-09 11:13:58,328:INFO: umap: Not installed +2023-11-09 11:13:58,328:INFO: ydata_profiling: Not installed +2023-11-09 11:13:58,328:INFO: explainerdashboard: Not installed +2023-11-09 11:13:58,329:INFO: autoviz: Not installed +2023-11-09 11:13:58,329:INFO: fairlearn: Not installed +2023-11-09 11:13:58,329:INFO: deepchecks: Not installed +2023-11-09 11:13:58,329:INFO: xgboost: Not installed +2023-11-09 11:13:58,329:INFO: catboost: Not installed +2023-11-09 11:13:58,329:INFO: kmodes: Not installed +2023-11-09 11:13:58,329:INFO: mlxtend: Not installed +2023-11-09 11:13:58,329:INFO: statsforecast: Not installed +2023-11-09 11:13:58,329:INFO: tune_sklearn: Not installed +2023-11-09 11:13:58,329:INFO: ray: Not installed +2023-11-09 11:13:58,329:INFO: hyperopt: Not installed +2023-11-09 11:13:58,329:INFO: optuna: Not installed +2023-11-09 11:13:58,329:INFO: skopt: Not installed +2023-11-09 11:13:58,329:INFO: mlflow: Not installed +2023-11-09 11:13:58,329:INFO: gradio: Not installed +2023-11-09 11:13:58,329:INFO: fastapi: Not installed +2023-11-09 11:13:58,329:INFO: uvicorn: Not installed +2023-11-09 11:13:58,329:INFO: m2cgen: Not installed +2023-11-09 11:13:58,329:INFO: evidently: Not installed +2023-11-09 11:13:58,329:INFO: fugue: Not installed +2023-11-09 11:13:58,330:INFO: streamlit: Not installed +2023-11-09 11:13:58,330:INFO: prophet: Not installed +2023-11-09 11:13:58,330:INFO:None +2023-11-09 11:13:58,330:INFO:Set up data. +2023-11-09 11:13:58,333:INFO:Set up folding strategy. +2023-11-09 11:13:58,333:INFO:Set up train/test split. +2023-11-09 11:13:58,333:INFO:Set up data. +2023-11-09 11:13:58,336:INFO:Set up index. +2023-11-09 11:13:58,337:INFO:Assigning column types. +2023-11-09 11:13:58,339:INFO:Engine successfully changes for model 'lr' to 'sklearn'. +2023-11-09 11:13:58,339:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,343:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,348:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,426:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,528:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,530:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:58,530:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:58,531:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,537:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,543:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,623:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,685:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,686:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:58,686:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:58,686:INFO:Engine successfully changes for model 'lasso' to 'sklearn'. +2023-11-09 11:13:58,691:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,705:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,826:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,868:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,869:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:58,869:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:58,875:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,880:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,939:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,976:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:13:58,977:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:58,977:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:58,977:INFO:Engine successfully changes for model 'ridge' to 'sklearn'. +2023-11-09 11:13:58,985:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:13:59,037:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:13:59,074:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:13:59,075:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,075:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,084:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:13:59,133:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:13:59,172:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:13:59,172:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,173:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,173:INFO:Engine successfully changes for model 'en' to 'sklearn'. +2023-11-09 11:13:59,230:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:13:59,269:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:13:59,270:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,270:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,327:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:13:59,366:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:13:59,367:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,367:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,367:INFO:Engine successfully changes for model 'knn' to 'sklearn'. +2023-11-09 11:13:59,425:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:13:59,463:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,463:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,522:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:13:59,566:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,566:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,567:INFO:Engine successfully changes for model 'svm' to 'sklearn'. +2023-11-09 11:13:59,664:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,664:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,760:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,760:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,761:INFO:Preparing preprocessing pipeline... +2023-11-09 11:13:59,761:INFO:Set up target transformation. +2023-11-09 11:13:59,761:INFO:Set up simple imputation. +2023-11-09 11:13:59,762:INFO:Set up column name cleaning. +2023-11-09 11:13:59,786:INFO:Finished creating preprocessing pipeline. +2023-11-09 11:13:59,793:INFO:Pipeline: Pipeline(memory=FastMemory(location=/tmp/joblib), + steps=[('target_transformation', + TransformerWrapperWithInverse(transformer=TargetTransformer(estimator=PowerTransformer(standardize=False)))), + ('numerical_imputer', + TransformerWrapper(include=['Year', 'Series'], + transformer=SimpleImputer())), + ('categorical_imputer', + TransformerWrapper(include=[], + transformer=SimpleImputer(strategy='most_frequent'))), + ('clean_column_names', + TransformerWrapper(transformer=CleanColumnNames()))]) +2023-11-09 11:13:59,793:INFO:Creating final display dataframe. +2023-11-09 11:13:59,870:INFO:Setup _display_container: Description Value +0 Session id 123 +1 Target Average price All property types +2 Target type Regression +3 Original data shape (271, 4) +4 Transformed data shape (271, 4) +5 Transformed train set shape (168, 4) +6 Transformed test set shape (103, 4) +7 Numeric features 2 +8 Preprocess True +9 Imputation type simple +10 Numeric imputation mean +11 Categorical imputation mode +12 Transform target True +13 Transform target method yeo-johnson +14 Fold Generator TimeSeriesSplit +15 Fold Number 3 +16 CPU Jobs -1 +17 Use GPU False +18 Log Experiment False +19 Experiment Name reg-default-name +20 USI a563 +2023-11-09 11:13:59,988:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:13:59,989:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:14:00,161:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:14:00,161:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:14:00,162:INFO:setup() successfully completed in 1.84s............... +2023-11-09 11:14:03,366:INFO:Initializing compare_models() +2023-11-09 11:14:03,367:INFO:compare_models(self=, include=None, fold=None, round=4, cross_validation=True, sort=MAE, n_select=1, budget_time=None, turbo=True, errors=ignore, fit_kwargs=None, groups=None, experiment_custom_tags=None, probability_threshold=None, verbose=True, parallel=None, caller_params={'self': , 'include': None, 'exclude': None, 'fold': None, 'round': 4, 'cross_validation': True, 'sort': 'MAE', 'n_select': 1, 'budget_time': None, 'turbo': True, 'errors': 'ignore', 'fit_kwargs': None, 'groups': None, 'experiment_custom_tags': None, 'engine': None, 'verbose': True, 'parallel': None, '__class__': }, exclude=None) +2023-11-09 11:14:03,368:INFO:Checking exceptions +2023-11-09 11:14:03,369:INFO:Preparing display monitor +2023-11-09 11:14:03,391:INFO:Initializing Linear Regression +2023-11-09 11:14:03,391:INFO:Total runtime is 4.434585571289063e-06 minutes +2023-11-09 11:14:03,394:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:03,394:INFO:Initializing create_model() +2023-11-09 11:14:03,395:INFO:create_model(self=, estimator=lr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:03,395:INFO:Checking exceptions +2023-11-09 11:14:03,395:INFO:Importing libraries +2023-11-09 11:14:03,395:INFO:Copying training dataset +2023-11-09 11:14:03,398:INFO:Defining folds +2023-11-09 11:14:03,398:INFO:Declaring metric variables +2023-11-09 11:14:03,402:INFO:Importing untrained model +2023-11-09 11:14:03,405:INFO:Linear Regression Imported successfully +2023-11-09 11:14:03,411:INFO:Starting cross validation +2023-11-09 11:14:03,412:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:03,507:INFO:Calculating mean and std +2023-11-09 11:14:03,507:INFO:Creating metrics dataframe +2023-11-09 11:14:03,512:INFO:Uploading results into container +2023-11-09 11:14:03,516:INFO:Uploading model into container now +2023-11-09 11:14:03,516:INFO:_master_model_container: 1 +2023-11-09 11:14:03,519:INFO:_display_container: 2 +2023-11-09 11:14:03,519:INFO:LinearRegression(n_jobs=-1) +2023-11-09 11:14:03,519:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:03,696:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:03,696:INFO:Creating metrics dataframe +2023-11-09 11:14:03,703:INFO:Initializing Lasso Regression +2023-11-09 11:14:03,704:INFO:Total runtime is 0.005212752024332682 minutes +2023-11-09 11:14:03,710:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:03,710:INFO:Initializing create_model() +2023-11-09 11:14:03,710:INFO:create_model(self=, estimator=lasso, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:03,710:INFO:Checking exceptions +2023-11-09 11:14:03,710:INFO:Importing libraries +2023-11-09 11:14:03,710:INFO:Copying training dataset +2023-11-09 11:14:03,714:INFO:Defining folds +2023-11-09 11:14:03,714:INFO:Declaring metric variables +2023-11-09 11:14:03,717:INFO:Importing untrained model +2023-11-09 11:14:03,720:INFO:Lasso Regression Imported successfully +2023-11-09 11:14:03,726:INFO:Starting cross validation +2023-11-09 11:14:03,727:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:03,801:WARNING:/workspaces/D2I-Jupyter-Notebook-Tools/.conda/lib/python3.8/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.575e+29, tolerance: 1.147e+26 + model = cd_fast.enet_coordinate_descent( + +2023-11-09 11:14:03,814:INFO:Calculating mean and std +2023-11-09 11:14:03,815:INFO:Creating metrics dataframe +2023-11-09 11:14:03,819:INFO:Uploading results into container +2023-11-09 11:14:03,820:INFO:Uploading model into container now +2023-11-09 11:14:03,820:INFO:_master_model_container: 2 +2023-11-09 11:14:03,820:INFO:_display_container: 2 +2023-11-09 11:14:03,820:INFO:Lasso(random_state=123) +2023-11-09 11:14:03,820:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:03,981:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:03,981:INFO:Creating metrics dataframe +2023-11-09 11:14:03,989:INFO:Initializing Ridge Regression +2023-11-09 11:14:03,989:INFO:Total runtime is 0.009976108868916828 minutes +2023-11-09 11:14:03,993:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:03,994:INFO:Initializing create_model() +2023-11-09 11:14:03,994:INFO:create_model(self=, estimator=ridge, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:03,994:INFO:Checking exceptions +2023-11-09 11:14:03,994:INFO:Importing libraries +2023-11-09 11:14:03,994:INFO:Copying training dataset +2023-11-09 11:14:03,997:INFO:Defining folds +2023-11-09 11:14:03,997:INFO:Declaring metric variables +2023-11-09 11:14:04,001:INFO:Importing untrained model +2023-11-09 11:14:04,005:INFO:Ridge Regression Imported successfully +2023-11-09 11:14:04,012:INFO:Starting cross validation +2023-11-09 11:14:04,013:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:04,095:INFO:Calculating mean and std +2023-11-09 11:14:04,095:INFO:Creating metrics dataframe +2023-11-09 11:14:04,098:INFO:Uploading results into container +2023-11-09 11:14:04,099:INFO:Uploading model into container now +2023-11-09 11:14:04,099:INFO:_master_model_container: 3 +2023-11-09 11:14:04,099:INFO:_display_container: 2 +2023-11-09 11:14:04,099:INFO:Ridge(random_state=123) +2023-11-09 11:14:04,099:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:04,227:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:04,227:INFO:Creating metrics dataframe +2023-11-09 11:14:04,235:INFO:Initializing Elastic Net +2023-11-09 11:14:04,235:INFO:Total runtime is 0.014074321587880452 minutes +2023-11-09 11:14:04,239:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:04,239:INFO:Initializing create_model() +2023-11-09 11:14:04,239:INFO:create_model(self=, estimator=en, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:04,239:INFO:Checking exceptions +2023-11-09 11:14:04,239:INFO:Importing libraries +2023-11-09 11:14:04,239:INFO:Copying training dataset +2023-11-09 11:14:04,242:INFO:Defining folds +2023-11-09 11:14:04,242:INFO:Declaring metric variables +2023-11-09 11:14:04,245:INFO:Importing untrained model +2023-11-09 11:14:04,248:INFO:Elastic Net Imported successfully +2023-11-09 11:14:04,254:INFO:Starting cross validation +2023-11-09 11:14:04,255:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:04,333:INFO:Calculating mean and std +2023-11-09 11:14:04,334:INFO:Creating metrics dataframe +2023-11-09 11:14:04,338:INFO:Uploading results into container +2023-11-09 11:14:04,338:INFO:Uploading model into container now +2023-11-09 11:14:04,339:INFO:_master_model_container: 4 +2023-11-09 11:14:04,339:INFO:_display_container: 2 +2023-11-09 11:14:04,339:INFO:ElasticNet(random_state=123) +2023-11-09 11:14:04,339:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:04,470:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:04,470:INFO:Creating metrics dataframe +2023-11-09 11:14:04,483:INFO:Initializing Least Angle Regression +2023-11-09 11:14:04,483:INFO:Total runtime is 0.018196769555409747 minutes +2023-11-09 11:14:04,488:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:04,488:INFO:Initializing create_model() +2023-11-09 11:14:04,488:INFO:create_model(self=, estimator=lar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:04,488:INFO:Checking exceptions +2023-11-09 11:14:04,488:INFO:Importing libraries +2023-11-09 11:14:04,489:INFO:Copying training dataset +2023-11-09 11:14:04,493:INFO:Defining folds +2023-11-09 11:14:04,494:INFO:Declaring metric variables +2023-11-09 11:14:04,498:INFO:Importing untrained model +2023-11-09 11:14:04,503:INFO:Least Angle Regression Imported successfully +2023-11-09 11:14:04,511:INFO:Starting cross validation +2023-11-09 11:14:04,514:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:04,617:INFO:Calculating mean and std +2023-11-09 11:14:04,618:INFO:Creating metrics dataframe +2023-11-09 11:14:04,624:INFO:Uploading results into container +2023-11-09 11:14:04,625:INFO:Uploading model into container now +2023-11-09 11:14:04,625:INFO:_master_model_container: 5 +2023-11-09 11:14:04,625:INFO:_display_container: 2 +2023-11-09 11:14:04,627:INFO:Lars(random_state=123) +2023-11-09 11:14:04,627:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:04,750:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:04,751:INFO:Creating metrics dataframe +2023-11-09 11:14:04,760:INFO:Initializing Lasso Least Angle Regression +2023-11-09 11:14:04,760:INFO:Total runtime is 0.022819622357686357 minutes +2023-11-09 11:14:04,763:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:04,764:INFO:Initializing create_model() +2023-11-09 11:14:04,764:INFO:create_model(self=, estimator=llar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:04,764:INFO:Checking exceptions +2023-11-09 11:14:04,765:INFO:Importing libraries +2023-11-09 11:14:04,765:INFO:Copying training dataset +2023-11-09 11:14:04,768:INFO:Defining folds +2023-11-09 11:14:04,768:INFO:Declaring metric variables +2023-11-09 11:14:04,772:INFO:Importing untrained model +2023-11-09 11:14:04,775:INFO:Lasso Least Angle Regression Imported successfully +2023-11-09 11:14:04,781:INFO:Starting cross validation +2023-11-09 11:14:04,782:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:04,853:INFO:Calculating mean and std +2023-11-09 11:14:04,854:INFO:Creating metrics dataframe +2023-11-09 11:14:04,856:INFO:Uploading results into container +2023-11-09 11:14:04,857:INFO:Uploading model into container now +2023-11-09 11:14:04,857:INFO:_master_model_container: 6 +2023-11-09 11:14:04,857:INFO:_display_container: 2 +2023-11-09 11:14:04,858:INFO:LassoLars(random_state=123) +2023-11-09 11:14:04,858:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:04,980:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:04,980:INFO:Creating metrics dataframe +2023-11-09 11:14:04,989:INFO:Initializing Orthogonal Matching Pursuit +2023-11-09 11:14:04,990:INFO:Total runtime is 0.02664367357889811 minutes +2023-11-09 11:14:04,994:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:04,995:INFO:Initializing create_model() +2023-11-09 11:14:04,995:INFO:create_model(self=, estimator=omp, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:04,995:INFO:Checking exceptions +2023-11-09 11:14:04,995:INFO:Importing libraries +2023-11-09 11:14:04,995:INFO:Copying training dataset +2023-11-09 11:14:05,001:INFO:Defining folds +2023-11-09 11:14:05,001:INFO:Declaring metric variables +2023-11-09 11:14:05,005:INFO:Importing untrained model +2023-11-09 11:14:05,009:INFO:Orthogonal Matching Pursuit Imported successfully +2023-11-09 11:14:05,017:INFO:Starting cross validation +2023-11-09 11:14:05,018:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:05,104:INFO:Calculating mean and std +2023-11-09 11:14:05,105:INFO:Creating metrics dataframe +2023-11-09 11:14:05,108:INFO:Uploading results into container +2023-11-09 11:14:05,109:INFO:Uploading model into container now +2023-11-09 11:14:05,109:INFO:_master_model_container: 7 +2023-11-09 11:14:05,110:INFO:_display_container: 2 +2023-11-09 11:14:05,110:INFO:OrthogonalMatchingPursuit() +2023-11-09 11:14:05,110:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:05,235:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:05,235:INFO:Creating metrics dataframe +2023-11-09 11:14:05,245:INFO:Initializing Bayesian Ridge +2023-11-09 11:14:05,245:INFO:Total runtime is 0.03090266386667887 minutes +2023-11-09 11:14:05,249:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:05,250:INFO:Initializing create_model() +2023-11-09 11:14:05,250:INFO:create_model(self=, estimator=br, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:05,250:INFO:Checking exceptions +2023-11-09 11:14:05,250:INFO:Importing libraries +2023-11-09 11:14:05,250:INFO:Copying training dataset +2023-11-09 11:14:05,254:INFO:Defining folds +2023-11-09 11:14:05,254:INFO:Declaring metric variables +2023-11-09 11:14:05,258:INFO:Importing untrained model +2023-11-09 11:14:05,262:INFO:Bayesian Ridge Imported successfully +2023-11-09 11:14:05,269:INFO:Starting cross validation +2023-11-09 11:14:05,270:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:05,368:INFO:Calculating mean and std +2023-11-09 11:14:05,369:INFO:Creating metrics dataframe +2023-11-09 11:14:05,376:INFO:Uploading results into container +2023-11-09 11:14:05,376:INFO:Uploading model into container now +2023-11-09 11:14:05,377:INFO:_master_model_container: 8 +2023-11-09 11:14:05,377:INFO:_display_container: 2 +2023-11-09 11:14:05,377:INFO:BayesianRidge() +2023-11-09 11:14:05,377:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:05,513:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:05,514:INFO:Creating metrics dataframe +2023-11-09 11:14:05,523:INFO:Initializing Passive Aggressive Regressor +2023-11-09 11:14:05,523:INFO:Total runtime is 0.0355341633160909 minutes +2023-11-09 11:14:05,526:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:05,527:INFO:Initializing create_model() +2023-11-09 11:14:05,527:INFO:create_model(self=, estimator=par, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:05,527:INFO:Checking exceptions +2023-11-09 11:14:05,527:INFO:Importing libraries +2023-11-09 11:14:05,527:INFO:Copying training dataset +2023-11-09 11:14:05,531:INFO:Defining folds +2023-11-09 11:14:05,531:INFO:Declaring metric variables +2023-11-09 11:14:05,534:INFO:Importing untrained model +2023-11-09 11:14:05,538:INFO:Passive Aggressive Regressor Imported successfully +2023-11-09 11:14:05,545:INFO:Starting cross validation +2023-11-09 11:14:05,546:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:05,608:WARNING:/workspaces/D2I-Jupyter-Notebook-Tools/.conda/lib/python3.8/site-packages/sklearn/linear_model/_stochastic_gradient.py:1548: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit. + warnings.warn( + +2023-11-09 11:14:05,622:INFO:Calculating mean and std +2023-11-09 11:14:05,623:INFO:Creating metrics dataframe +2023-11-09 11:14:05,626:INFO:Uploading results into container +2023-11-09 11:14:05,627:INFO:Uploading model into container now +2023-11-09 11:14:05,627:INFO:_master_model_container: 9 +2023-11-09 11:14:05,627:INFO:_display_container: 2 +2023-11-09 11:14:05,628:INFO:PassiveAggressiveRegressor(random_state=123) +2023-11-09 11:14:05,628:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:05,756:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:05,757:INFO:Creating metrics dataframe +2023-11-09 11:14:05,766:INFO:Initializing Huber Regressor +2023-11-09 11:14:05,766:INFO:Total runtime is 0.03959020773569742 minutes +2023-11-09 11:14:05,770:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:05,770:INFO:Initializing create_model() +2023-11-09 11:14:05,770:INFO:create_model(self=, estimator=huber, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:05,770:INFO:Checking exceptions +2023-11-09 11:14:05,770:INFO:Importing libraries +2023-11-09 11:14:05,771:INFO:Copying training dataset +2023-11-09 11:14:05,774:INFO:Defining folds +2023-11-09 11:14:05,774:INFO:Declaring metric variables +2023-11-09 11:14:05,777:INFO:Importing untrained model +2023-11-09 11:14:05,781:INFO:Huber Regressor Imported successfully +2023-11-09 11:14:05,787:INFO:Starting cross validation +2023-11-09 11:14:05,788:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:05,893:INFO:Calculating mean and std +2023-11-09 11:14:05,895:INFO:Creating metrics dataframe +2023-11-09 11:14:05,898:INFO:Uploading results into container +2023-11-09 11:14:05,899:INFO:Uploading model into container now +2023-11-09 11:14:05,900:INFO:_master_model_container: 10 +2023-11-09 11:14:05,900:INFO:_display_container: 2 +2023-11-09 11:14:05,900:INFO:HuberRegressor() +2023-11-09 11:14:05,900:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:06,031:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:06,031:INFO:Creating metrics dataframe +2023-11-09 11:14:06,040:INFO:Initializing K Neighbors Regressor +2023-11-09 11:14:06,040:INFO:Total runtime is 0.04415459235509236 minutes +2023-11-09 11:14:06,044:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:06,044:INFO:Initializing create_model() +2023-11-09 11:14:06,044:INFO:create_model(self=, estimator=knn, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:06,044:INFO:Checking exceptions +2023-11-09 11:14:06,044:INFO:Importing libraries +2023-11-09 11:14:06,045:INFO:Copying training dataset +2023-11-09 11:14:06,049:INFO:Defining folds +2023-11-09 11:14:06,049:INFO:Declaring metric variables +2023-11-09 11:14:06,053:INFO:Importing untrained model +2023-11-09 11:14:06,057:INFO:K Neighbors Regressor Imported successfully +2023-11-09 11:14:06,064:INFO:Starting cross validation +2023-11-09 11:14:06,065:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:06,157:INFO:Calculating mean and std +2023-11-09 11:14:06,158:INFO:Creating metrics dataframe +2023-11-09 11:14:06,162:INFO:Uploading results into container +2023-11-09 11:14:06,163:INFO:Uploading model into container now +2023-11-09 11:14:06,163:INFO:_master_model_container: 11 +2023-11-09 11:14:06,163:INFO:_display_container: 2 +2023-11-09 11:14:06,164:INFO:KNeighborsRegressor(n_jobs=-1) +2023-11-09 11:14:06,164:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:06,301:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:06,301:INFO:Creating metrics dataframe +2023-11-09 11:14:06,311:INFO:Initializing Decision Tree Regressor +2023-11-09 11:14:06,311:INFO:Total runtime is 0.04867283105850219 minutes +2023-11-09 11:14:06,315:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:06,315:INFO:Initializing create_model() +2023-11-09 11:14:06,315:INFO:create_model(self=, estimator=dt, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:06,315:INFO:Checking exceptions +2023-11-09 11:14:06,316:INFO:Importing libraries +2023-11-09 11:14:06,316:INFO:Copying training dataset +2023-11-09 11:14:06,319:INFO:Defining folds +2023-11-09 11:14:06,319:INFO:Declaring metric variables +2023-11-09 11:14:06,323:INFO:Importing untrained model +2023-11-09 11:14:06,326:INFO:Decision Tree Regressor Imported successfully +2023-11-09 11:14:06,332:INFO:Starting cross validation +2023-11-09 11:14:06,334:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:06,406:INFO:Calculating mean and std +2023-11-09 11:14:06,406:INFO:Creating metrics dataframe +2023-11-09 11:14:06,409:INFO:Uploading results into container +2023-11-09 11:14:06,409:INFO:Uploading model into container now +2023-11-09 11:14:06,410:INFO:_master_model_container: 12 +2023-11-09 11:14:06,410:INFO:_display_container: 2 +2023-11-09 11:14:06,410:INFO:DecisionTreeRegressor(random_state=123) +2023-11-09 11:14:06,410:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:06,535:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:06,535:INFO:Creating metrics dataframe +2023-11-09 11:14:06,545:INFO:Initializing Random Forest Regressor +2023-11-09 11:14:06,546:INFO:Total runtime is 0.05258002678553263 minutes +2023-11-09 11:14:06,549:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:06,550:INFO:Initializing create_model() +2023-11-09 11:14:06,550:INFO:create_model(self=, estimator=rf, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:06,550:INFO:Checking exceptions +2023-11-09 11:14:06,550:INFO:Importing libraries +2023-11-09 11:14:06,550:INFO:Copying training dataset +2023-11-09 11:14:06,553:INFO:Defining folds +2023-11-09 11:14:06,554:INFO:Declaring metric variables +2023-11-09 11:14:06,557:INFO:Importing untrained model +2023-11-09 11:14:06,560:INFO:Random Forest Regressor Imported successfully +2023-11-09 11:14:06,566:INFO:Starting cross validation +2023-11-09 11:14:06,567:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:07,008:INFO:Calculating mean and std +2023-11-09 11:14:07,009:INFO:Creating metrics dataframe +2023-11-09 11:14:07,012:INFO:Uploading results into container +2023-11-09 11:14:07,013:INFO:Uploading model into container now +2023-11-09 11:14:07,014:INFO:_master_model_container: 13 +2023-11-09 11:14:07,014:INFO:_display_container: 2 +2023-11-09 11:14:07,014:INFO:RandomForestRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:14:07,014:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:07,147:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:07,148:INFO:Creating metrics dataframe +2023-11-09 11:14:07,157:INFO:Initializing Extra Trees Regressor +2023-11-09 11:14:07,158:INFO:Total runtime is 0.06277682781219482 minutes +2023-11-09 11:14:07,161:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:07,161:INFO:Initializing create_model() +2023-11-09 11:14:07,162:INFO:create_model(self=, estimator=et, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:07,162:INFO:Checking exceptions +2023-11-09 11:14:07,162:INFO:Importing libraries +2023-11-09 11:14:07,162:INFO:Copying training dataset +2023-11-09 11:14:07,165:INFO:Defining folds +2023-11-09 11:14:07,165:INFO:Declaring metric variables +2023-11-09 11:14:07,169:INFO:Importing untrained model +2023-11-09 11:14:07,172:INFO:Extra Trees Regressor Imported successfully +2023-11-09 11:14:07,178:INFO:Starting cross validation +2023-11-09 11:14:07,180:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:07,504:INFO:Calculating mean and std +2023-11-09 11:14:07,505:INFO:Creating metrics dataframe +2023-11-09 11:14:07,512:INFO:Uploading results into container +2023-11-09 11:14:07,514:INFO:Uploading model into container now +2023-11-09 11:14:07,515:INFO:_master_model_container: 14 +2023-11-09 11:14:07,515:INFO:_display_container: 2 +2023-11-09 11:14:07,516:INFO:ExtraTreesRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:14:07,517:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:07,646:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:07,646:INFO:Creating metrics dataframe +2023-11-09 11:14:07,656:INFO:Initializing AdaBoost Regressor +2023-11-09 11:14:07,657:INFO:Total runtime is 0.07109393676122029 minutes +2023-11-09 11:14:07,660:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:07,661:INFO:Initializing create_model() +2023-11-09 11:14:07,661:INFO:create_model(self=, estimator=ada, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:07,661:INFO:Checking exceptions +2023-11-09 11:14:07,661:INFO:Importing libraries +2023-11-09 11:14:07,661:INFO:Copying training dataset +2023-11-09 11:14:07,664:INFO:Defining folds +2023-11-09 11:14:07,665:INFO:Declaring metric variables +2023-11-09 11:14:07,668:INFO:Importing untrained model +2023-11-09 11:14:07,672:INFO:AdaBoost Regressor Imported successfully +2023-11-09 11:14:07,678:INFO:Starting cross validation +2023-11-09 11:14:07,679:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:07,848:INFO:Calculating mean and std +2023-11-09 11:14:07,849:INFO:Creating metrics dataframe +2023-11-09 11:14:07,853:INFO:Uploading results into container +2023-11-09 11:14:07,853:INFO:Uploading model into container now +2023-11-09 11:14:07,854:INFO:_master_model_container: 15 +2023-11-09 11:14:07,854:INFO:_display_container: 2 +2023-11-09 11:14:07,854:INFO:AdaBoostRegressor(random_state=123) +2023-11-09 11:14:07,854:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:07,985:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:07,985:INFO:Creating metrics dataframe +2023-11-09 11:14:07,995:INFO:Initializing Gradient Boosting Regressor +2023-11-09 11:14:07,995:INFO:Total runtime is 0.07673628330230713 minutes +2023-11-09 11:14:07,999:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:07,999:INFO:Initializing create_model() +2023-11-09 11:14:07,999:INFO:create_model(self=, estimator=gbr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:07,999:INFO:Checking exceptions +2023-11-09 11:14:07,999:INFO:Importing libraries +2023-11-09 11:14:07,999:INFO:Copying training dataset +2023-11-09 11:14:08,003:INFO:Defining folds +2023-11-09 11:14:08,003:INFO:Declaring metric variables +2023-11-09 11:14:08,007:INFO:Importing untrained model +2023-11-09 11:14:08,010:INFO:Gradient Boosting Regressor Imported successfully +2023-11-09 11:14:08,016:INFO:Starting cross validation +2023-11-09 11:14:08,017:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:08,176:INFO:Calculating mean and std +2023-11-09 11:14:08,177:INFO:Creating metrics dataframe +2023-11-09 11:14:08,181:INFO:Uploading results into container +2023-11-09 11:14:08,182:INFO:Uploading model into container now +2023-11-09 11:14:08,182:INFO:_master_model_container: 16 +2023-11-09 11:14:08,182:INFO:_display_container: 2 +2023-11-09 11:14:08,183:INFO:GradientBoostingRegressor(random_state=123) +2023-11-09 11:14:08,183:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:08,307:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:08,307:INFO:Creating metrics dataframe +2023-11-09 11:14:08,319:INFO:Initializing Light Gradient Boosting Machine +2023-11-09 11:14:08,319:INFO:Total runtime is 0.08212989171346029 minutes +2023-11-09 11:14:08,323:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:08,323:INFO:Initializing create_model() +2023-11-09 11:14:08,323:INFO:create_model(self=, estimator=lightgbm, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:08,323:INFO:Checking exceptions +2023-11-09 11:14:08,324:INFO:Importing libraries +2023-11-09 11:14:08,324:INFO:Copying training dataset +2023-11-09 11:14:08,327:INFO:Defining folds +2023-11-09 11:14:08,328:INFO:Declaring metric variables +2023-11-09 11:14:08,332:INFO:Importing untrained model +2023-11-09 11:14:08,335:INFO:Light Gradient Boosting Machine Imported successfully +2023-11-09 11:14:08,341:INFO:Starting cross validation +2023-11-09 11:14:08,342:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:08,497:INFO:Calculating mean and std +2023-11-09 11:14:08,498:INFO:Creating metrics dataframe +2023-11-09 11:14:08,504:INFO:Uploading results into container +2023-11-09 11:14:08,504:INFO:Uploading model into container now +2023-11-09 11:14:08,505:INFO:_master_model_container: 17 +2023-11-09 11:14:08,505:INFO:_display_container: 2 +2023-11-09 11:14:08,505:INFO:LGBMRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:14:08,505:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:08,628:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:08,628:INFO:Creating metrics dataframe +2023-11-09 11:14:08,639:INFO:Initializing Dummy Regressor +2023-11-09 11:14:08,639:INFO:Total runtime is 0.08746862411499023 minutes +2023-11-09 11:14:08,643:INFO:SubProcess create_model() called ================================== +2023-11-09 11:14:08,643:INFO:Initializing create_model() +2023-11-09 11:14:08,643:INFO:create_model(self=, estimator=dummy, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:08,643:INFO:Checking exceptions +2023-11-09 11:14:08,644:INFO:Importing libraries +2023-11-09 11:14:08,644:INFO:Copying training dataset +2023-11-09 11:14:08,647:INFO:Defining folds +2023-11-09 11:14:08,647:INFO:Declaring metric variables +2023-11-09 11:14:08,650:INFO:Importing untrained model +2023-11-09 11:14:08,653:INFO:Dummy Regressor Imported successfully +2023-11-09 11:14:08,659:INFO:Starting cross validation +2023-11-09 11:14:08,660:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:14:08,731:INFO:Calculating mean and std +2023-11-09 11:14:08,731:INFO:Creating metrics dataframe +2023-11-09 11:14:08,734:INFO:Uploading results into container +2023-11-09 11:14:08,735:INFO:Uploading model into container now +2023-11-09 11:14:08,735:INFO:_master_model_container: 18 +2023-11-09 11:14:08,735:INFO:_display_container: 2 +2023-11-09 11:14:08,735:INFO:DummyRegressor() +2023-11-09 11:14:08,735:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:08,890:INFO:SubProcess create_model() end ================================== +2023-11-09 11:14:08,890:INFO:Creating metrics dataframe +2023-11-09 11:14:08,920:INFO:Initializing create_model() +2023-11-09 11:14:08,920:INFO:create_model(self=, estimator=LGBMRegressor(n_jobs=-1, random_state=123), fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=False, predict=False, fit_kwargs={}, groups=None, refit=True, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=None, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:14:08,920:INFO:Checking exceptions +2023-11-09 11:14:08,921:INFO:Importing libraries +2023-11-09 11:14:08,921:INFO:Copying training dataset +2023-11-09 11:14:08,924:INFO:Defining folds +2023-11-09 11:14:08,924:INFO:Declaring metric variables +2023-11-09 11:14:08,925:INFO:Importing untrained model +2023-11-09 11:14:08,925:INFO:Declaring custom model +2023-11-09 11:14:08,925:INFO:Light Gradient Boosting Machine Imported successfully +2023-11-09 11:14:08,926:INFO:Cross validation set to False +2023-11-09 11:14:08,926:INFO:Fitting Model +2023-11-09 11:14:08,971:INFO:[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000037 seconds. +2023-11-09 11:14:08,973:INFO:You can set `force_col_wise=true` to remove the overhead. +2023-11-09 11:14:08,974:INFO:[LightGBM] [Info] Total Bins 85 +2023-11-09 11:14:08,975:INFO:[LightGBM] [Info] Number of data points in the train set: 168, number of used features: 3 +2023-11-09 11:14:08,976:INFO:[LightGBM] [Info] Start training from score 7743509295166477312.000000 +2023-11-09 11:14:08,977:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,978:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,979:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,981:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,981:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,982:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,988:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,989:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,990:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,994:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,994:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,995:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,995:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,995:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,995:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,996:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,996:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,996:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:08,997:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,000:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,001:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,004:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,006:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,020:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,021:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,021:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,021:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,021:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,022:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,022:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,022:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,023:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,024:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,026:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,027:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,046:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,046:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,046:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,047:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,047:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,047:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,048:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,048:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,048:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,048:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,049:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,049:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,049:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,050:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,050:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,050:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,050:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,051:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,051:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,051:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,051:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,052:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,052:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,052:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,053:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,053:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,053:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,053:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,054:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,054:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,054:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,054:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,055:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,055:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,055:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,055:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,056:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,056:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,056:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,056:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,057:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,057:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,057:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,057:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,058:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,058:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,058:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,058:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,059:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,059:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,059:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,059:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,060:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,060:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,060:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,060:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,060:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,061:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,061:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,061:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,061:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,062:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,062:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,062:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,062:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf +2023-11-09 11:14:09,066:INFO:LGBMRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:14:09,066:INFO:create_model() successfully completed...................................... +2023-11-09 11:14:09,230:INFO:_master_model_container: 18 +2023-11-09 11:14:09,230:INFO:_display_container: 2 +2023-11-09 11:14:09,230:INFO:LGBMRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:14:09,231:INFO:compare_models() successfully completed...................................... +2023-11-09 11:14:16,296:INFO:Initializing predict_model() +2023-11-09 11:14:16,297:INFO:predict_model(self=, estimator=LGBMRegressor(n_jobs=-1, random_state=123), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=.encode_labels at 0x7fbb2d2d58b0>) +2023-11-09 11:14:16,297:INFO:Checking exceptions +2023-11-09 11:14:16,297:INFO:Preloading libraries +2023-11-09 11:14:16,299:INFO:Set up data. +2023-11-09 11:14:16,302:INFO:Set up index. +2023-11-09 11:14:55,200:INFO:Initializing predict_model() +2023-11-09 11:14:55,201:INFO:predict_model(self=, estimator=LGBMRegressor(n_jobs=-1, random_state=123), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=.encode_labels at 0x7fbb44eba160>) +2023-11-09 11:14:55,201:INFO:Checking exceptions +2023-11-09 11:14:55,201:INFO:Preloading libraries +2023-11-09 11:14:55,203:INFO:Set up data. +2023-11-09 11:14:55,206:INFO:Set up index. +2023-11-09 11:15:19,601:INFO:PyCaret RegressionExperiment +2023-11-09 11:15:19,601:INFO:Logging name: reg-default-name +2023-11-09 11:15:19,601:INFO:ML Usecase: MLUsecase.REGRESSION +2023-11-09 11:15:19,601:INFO:version 3.1.0 +2023-11-09 11:15:19,601:INFO:Initializing setup() +2023-11-09 11:15:19,601:INFO:self.USI: e1b2 +2023-11-09 11:15:19,601:INFO:self._variable_keys: {'seed', 'idx', 'transform_target_param', 'gpu_param', 'target_param', 'log_plots_param', 'pipeline', 'logging_param', 'fold_groups_param', '_ml_usecase', 'html_param', 'gpu_n_jobs_param', 'y', 'y_test', 'y_train', 'memory', 'exp_id', 'X_test', 'exp_name_log', 'USI', 'data', 'X_train', 'fold_shuffle_param', 'X', 'fold_generator', 'n_jobs_param', '_available_plots'} +2023-11-09 11:15:19,601:INFO:Checking environment +2023-11-09 11:15:19,601:INFO:python_version: 3.8.18 +2023-11-09 11:15:19,601:INFO:python_build: ('default', 'Sep 11 2023 13:40:15') +2023-11-09 11:15:19,601:INFO:machine: x86_64 +2023-11-09 11:15:19,601:INFO:platform: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:15:19,602:INFO:Memory: svmem(total=8315187200, available=4601843712, percent=44.7, used=3378569216, free=269778944, active=1470234624, inactive=5726916608, buffers=334860288, cached=4331978752, shared=4485120, slab=651251712) +2023-11-09 11:15:19,602:INFO:Physical Core: 1 +2023-11-09 11:15:19,602:INFO:Logical Core: 2 +2023-11-09 11:15:19,602:INFO:Checking libraries +2023-11-09 11:15:19,602:INFO:System: +2023-11-09 11:15:19,602:INFO: python: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] +2023-11-09 11:15:19,602:INFO:executable: /workspaces/D2I-Jupyter-Notebook-Tools/.conda/bin/python +2023-11-09 11:15:19,602:INFO: machine: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:15:19,602:INFO:PyCaret required dependencies: +2023-11-09 11:15:19,602:INFO: pip: 23.3 +2023-11-09 11:15:19,602:INFO: setuptools: 68.0.0 +2023-11-09 11:15:19,602:INFO: pycaret: 3.1.0 +2023-11-09 11:15:19,603:INFO: IPython: 8.12.0 +2023-11-09 11:15:19,603:INFO: ipywidgets: 8.1.1 +2023-11-09 11:15:19,603:INFO: tqdm: 4.66.1 +2023-11-09 11:15:19,603:INFO: numpy: 1.23.5 +2023-11-09 11:15:19,603:INFO: pandas: 1.5.3 +2023-11-09 11:15:19,603:INFO: jinja2: 3.1.2 +2023-11-09 11:15:19,603:INFO: scipy: 1.10.1 +2023-11-09 11:15:19,603:INFO: joblib: 1.3.2 +2023-11-09 11:15:19,603:INFO: sklearn: 1.2.2 +2023-11-09 11:15:19,603:INFO: pyod: 1.1.1 +2023-11-09 11:15:19,603:INFO: imblearn: 0.11.0 +2023-11-09 11:15:19,603:INFO: category_encoders: 2.6.3 +2023-11-09 11:15:19,603:INFO: lightgbm: 4.1.0 +2023-11-09 11:15:19,603:INFO: numba: 0.58.1 +2023-11-09 11:15:19,603:INFO: requests: 2.31.0 +2023-11-09 11:15:19,603:INFO: matplotlib: 3.7.3 +2023-11-09 11:15:19,603:INFO: scikitplot: 0.3.7 +2023-11-09 11:15:19,603:INFO: yellowbrick: 1.5 +2023-11-09 11:15:19,603:INFO: plotly: 5.18.0 +2023-11-09 11:15:19,603:INFO: plotly-resampler: Not installed +2023-11-09 11:15:19,604:INFO: kaleido: 0.2.1 +2023-11-09 11:15:19,604:INFO: schemdraw: 0.15 +2023-11-09 11:15:19,604:INFO: statsmodels: 0.14.0 +2023-11-09 11:15:19,604:INFO: sktime: 0.21.1 +2023-11-09 11:15:19,604:INFO: tbats: 1.1.3 +2023-11-09 11:15:19,604:INFO: pmdarima: 2.0.4 +2023-11-09 11:15:19,604:INFO: psutil: 5.9.0 +2023-11-09 11:15:19,604:INFO: markupsafe: 2.1.3 +2023-11-09 11:15:19,604:INFO: pickle5: Not installed +2023-11-09 11:15:19,604:INFO: cloudpickle: 3.0.0 +2023-11-09 11:15:19,604:INFO: deprecation: 2.1.0 +2023-11-09 11:15:19,604:INFO: xxhash: 3.4.1 +2023-11-09 11:15:19,604:INFO: wurlitzer: 3.0.3 +2023-11-09 11:15:19,604:INFO:PyCaret optional dependencies: +2023-11-09 11:15:19,604:INFO: shap: Not installed +2023-11-09 11:15:19,604:INFO: interpret: Not installed +2023-11-09 11:15:19,604:INFO: umap: Not installed +2023-11-09 11:15:19,604:INFO: ydata_profiling: Not installed +2023-11-09 11:15:19,604:INFO: explainerdashboard: Not installed +2023-11-09 11:15:19,604:INFO: autoviz: Not installed +2023-11-09 11:15:19,605:INFO: fairlearn: Not installed +2023-11-09 11:15:19,605:INFO: deepchecks: Not installed +2023-11-09 11:15:19,605:INFO: xgboost: Not installed +2023-11-09 11:15:19,605:INFO: catboost: Not installed +2023-11-09 11:15:19,605:INFO: kmodes: Not installed +2023-11-09 11:15:19,605:INFO: mlxtend: Not installed +2023-11-09 11:15:19,605:INFO: statsforecast: Not installed +2023-11-09 11:15:19,605:INFO: tune_sklearn: Not installed +2023-11-09 11:15:19,605:INFO: ray: Not installed +2023-11-09 11:15:19,605:INFO: hyperopt: Not installed +2023-11-09 11:15:19,605:INFO: optuna: Not installed +2023-11-09 11:15:19,605:INFO: skopt: Not installed +2023-11-09 11:15:19,605:INFO: mlflow: Not installed +2023-11-09 11:15:19,605:INFO: gradio: Not installed +2023-11-09 11:15:19,605:INFO: fastapi: Not installed +2023-11-09 11:15:19,605:INFO: uvicorn: Not installed +2023-11-09 11:15:19,605:INFO: m2cgen: Not installed +2023-11-09 11:15:19,606:INFO: evidently: Not installed +2023-11-09 11:15:19,606:INFO: fugue: Not installed +2023-11-09 11:15:19,606:INFO: streamlit: Not installed +2023-11-09 11:15:19,606:INFO: prophet: Not installed +2023-11-09 11:15:19,606:INFO:None +2023-11-09 11:15:19,606:INFO:Set up data. +2023-11-09 11:15:19,609:INFO:Set up folding strategy. +2023-11-09 11:15:19,609:INFO:Set up train/test split. +2023-11-09 11:15:19,609:INFO:Set up data. +2023-11-09 11:15:19,613:INFO:Set up index. +2023-11-09 11:15:19,613:INFO:Assigning column types. +2023-11-09 11:15:19,615:INFO:Engine successfully changes for model 'lr' to 'sklearn'. +2023-11-09 11:15:19,615:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:15:19,619:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:15:19,623:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:15:19,677:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:15:19,747:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:15:19,748:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:19,748:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:19,749:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:15:19,757:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:15:19,764:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:15:19,901:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:15:19,954:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:15:19,955:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:19,955:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:19,955:INFO:Engine successfully changes for model 'lasso' to 'sklearn'. +2023-11-09 11:15:19,960:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:15:19,964:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,013:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,050:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,050:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,050:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,055:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,058:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,116:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,153:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,153:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,154:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,154:INFO:Engine successfully changes for model 'ridge' to 'sklearn'. +2023-11-09 11:15:20,163:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,211:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,250:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,250:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,250:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,258:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,305:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,346:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,346:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,346:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,347:INFO:Engine successfully changes for model 'en' to 'sklearn'. +2023-11-09 11:15:20,401:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,437:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,438:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,438:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,526:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,581:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,582:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,582:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,582:INFO:Engine successfully changes for model 'knn' to 'sklearn'. +2023-11-09 11:15:20,639:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,678:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,678:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,736:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:15:20,773:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,773:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,774:INFO:Engine successfully changes for model 'svm' to 'sklearn'. +2023-11-09 11:15:20,871:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,871:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,974:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,974:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:20,975:INFO:Preparing preprocessing pipeline... +2023-11-09 11:15:20,975:INFO:Set up target transformation. +2023-11-09 11:15:20,975:INFO:Set up simple imputation. +2023-11-09 11:15:20,976:INFO:Set up column name cleaning. +2023-11-09 11:15:21,005:INFO:Finished creating preprocessing pipeline. +2023-11-09 11:15:21,010:INFO:Pipeline: Pipeline(memory=FastMemory(location=/tmp/joblib), + steps=[('target_transformation', + TransformerWrapperWithInverse(transformer=TargetTransformer(estimator=PowerTransformer(standardize=False)))), + ('numerical_imputer', + TransformerWrapper(include=['Year', 'Series'], + transformer=SimpleImputer())), + ('categorical_imputer', + TransformerWrapper(include=[], + transformer=SimpleImputer(strategy='most_frequent'))), + ('clean_column_names', + TransformerWrapper(transformer=CleanColumnNames()))]) +2023-11-09 11:15:21,010:INFO:Creating final display dataframe. +2023-11-09 11:15:21,080:INFO:Setup _display_container: Description Value +0 Session id 123 +1 Target Average price All property types +2 Target type Regression +3 Original data shape (523, 4) +4 Transformed data shape (523, 4) +5 Transformed train set shape (372, 4) +6 Transformed test set shape (151, 4) +7 Numeric features 2 +8 Preprocess True +9 Imputation type simple +10 Numeric imputation mean +11 Categorical imputation mode +12 Transform target True +13 Transform target method yeo-johnson +14 Fold Generator TimeSeriesSplit +15 Fold Number 3 +16 CPU Jobs -1 +17 Use GPU False +18 Log Experiment False +19 Experiment Name reg-default-name +20 USI e1b2 +2023-11-09 11:15:21,196:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:21,196:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:21,293:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:21,293:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:15:21,294:INFO:setup() successfully completed in 1.69s............... +2023-11-09 11:15:21,384:INFO:Initializing compare_models() +2023-11-09 11:15:21,384:INFO:compare_models(self=, include=None, fold=None, round=4, cross_validation=True, sort=MAE, n_select=1, budget_time=None, turbo=True, errors=ignore, fit_kwargs=None, groups=None, experiment_custom_tags=None, probability_threshold=None, verbose=True, parallel=None, caller_params={'self': , 'include': None, 'exclude': None, 'fold': None, 'round': 4, 'cross_validation': True, 'sort': 'MAE', 'n_select': 1, 'budget_time': None, 'turbo': True, 'errors': 'ignore', 'fit_kwargs': None, 'groups': None, 'experiment_custom_tags': None, 'engine': None, 'verbose': True, 'parallel': None, '__class__': }, exclude=None) +2023-11-09 11:15:21,385:INFO:Checking exceptions +2023-11-09 11:15:21,386:INFO:Preparing display monitor +2023-11-09 11:15:21,409:INFO:Initializing Linear Regression +2023-11-09 11:15:21,409:INFO:Total runtime is 3.890196482340495e-06 minutes +2023-11-09 11:15:21,412:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:21,412:INFO:Initializing create_model() +2023-11-09 11:15:21,413:INFO:create_model(self=, estimator=lr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:21,413:INFO:Checking exceptions +2023-11-09 11:15:21,413:INFO:Importing libraries +2023-11-09 11:15:21,413:INFO:Copying training dataset +2023-11-09 11:15:21,416:INFO:Defining folds +2023-11-09 11:15:21,416:INFO:Declaring metric variables +2023-11-09 11:15:21,418:INFO:Importing untrained model +2023-11-09 11:15:21,422:INFO:Linear Regression Imported successfully +2023-11-09 11:15:21,429:INFO:Starting cross validation +2023-11-09 11:15:21,430:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:21,504:INFO:Calculating mean and std +2023-11-09 11:15:21,505:INFO:Creating metrics dataframe +2023-11-09 11:15:21,509:INFO:Uploading results into container +2023-11-09 11:15:21,509:INFO:Uploading model into container now +2023-11-09 11:15:21,510:INFO:_master_model_container: 1 +2023-11-09 11:15:21,510:INFO:_display_container: 2 +2023-11-09 11:15:21,510:INFO:LinearRegression(n_jobs=-1) +2023-11-09 11:15:21,510:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:21,642:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:21,642:INFO:Creating metrics dataframe +2023-11-09 11:15:21,650:INFO:Initializing Lasso Regression +2023-11-09 11:15:21,650:INFO:Total runtime is 0.004018759727478027 minutes +2023-11-09 11:15:21,653:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:21,654:INFO:Initializing create_model() +2023-11-09 11:15:21,654:INFO:create_model(self=, estimator=lasso, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:21,654:INFO:Checking exceptions +2023-11-09 11:15:21,654:INFO:Importing libraries +2023-11-09 11:15:21,654:INFO:Copying training dataset +2023-11-09 11:15:21,657:INFO:Defining folds +2023-11-09 11:15:21,657:INFO:Declaring metric variables +2023-11-09 11:15:21,660:INFO:Importing untrained model +2023-11-09 11:15:21,663:INFO:Lasso Regression Imported successfully +2023-11-09 11:15:21,669:INFO:Starting cross validation +2023-11-09 11:15:21,670:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:21,745:INFO:Calculating mean and std +2023-11-09 11:15:21,746:INFO:Creating metrics dataframe +2023-11-09 11:15:21,749:INFO:Uploading results into container +2023-11-09 11:15:21,749:INFO:Uploading model into container now +2023-11-09 11:15:21,750:INFO:_master_model_container: 2 +2023-11-09 11:15:21,750:INFO:_display_container: 2 +2023-11-09 11:15:21,750:INFO:Lasso(random_state=123) +2023-11-09 11:15:21,750:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:21,867:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:21,867:INFO:Creating metrics dataframe +2023-11-09 11:15:21,875:INFO:Initializing Ridge Regression +2023-11-09 11:15:21,875:INFO:Total runtime is 0.007770164807637532 minutes +2023-11-09 11:15:21,878:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:21,879:INFO:Initializing create_model() +2023-11-09 11:15:21,879:INFO:create_model(self=, estimator=ridge, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:21,879:INFO:Checking exceptions +2023-11-09 11:15:21,879:INFO:Importing libraries +2023-11-09 11:15:21,879:INFO:Copying training dataset +2023-11-09 11:15:21,882:INFO:Defining folds +2023-11-09 11:15:21,882:INFO:Declaring metric variables +2023-11-09 11:15:21,884:INFO:Importing untrained model +2023-11-09 11:15:21,887:INFO:Ridge Regression Imported successfully +2023-11-09 11:15:21,893:INFO:Starting cross validation +2023-11-09 11:15:21,894:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:21,988:INFO:Calculating mean and std +2023-11-09 11:15:21,989:INFO:Creating metrics dataframe +2023-11-09 11:15:21,994:INFO:Uploading results into container +2023-11-09 11:15:21,995:INFO:Uploading model into container now +2023-11-09 11:15:21,995:INFO:_master_model_container: 3 +2023-11-09 11:15:21,995:INFO:_display_container: 2 +2023-11-09 11:15:21,996:INFO:Ridge(random_state=123) +2023-11-09 11:15:21,996:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:22,197:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:22,197:INFO:Creating metrics dataframe +2023-11-09 11:15:22,206:INFO:Initializing Elastic Net +2023-11-09 11:15:22,206:INFO:Total runtime is 0.01328597068786621 minutes +2023-11-09 11:15:22,209:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:22,210:INFO:Initializing create_model() +2023-11-09 11:15:22,210:INFO:create_model(self=, estimator=en, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:22,210:INFO:Checking exceptions +2023-11-09 11:15:22,210:INFO:Importing libraries +2023-11-09 11:15:22,210:INFO:Copying training dataset +2023-11-09 11:15:22,213:INFO:Defining folds +2023-11-09 11:15:22,213:INFO:Declaring metric variables +2023-11-09 11:15:22,217:INFO:Importing untrained model +2023-11-09 11:15:22,228:INFO:Elastic Net Imported successfully +2023-11-09 11:15:22,245:INFO:Starting cross validation +2023-11-09 11:15:22,246:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:22,354:INFO:Calculating mean and std +2023-11-09 11:15:22,355:INFO:Creating metrics dataframe +2023-11-09 11:15:22,362:INFO:Uploading results into container +2023-11-09 11:15:22,363:INFO:Uploading model into container now +2023-11-09 11:15:22,363:INFO:_master_model_container: 4 +2023-11-09 11:15:22,364:INFO:_display_container: 2 +2023-11-09 11:15:22,364:INFO:ElasticNet(random_state=123) +2023-11-09 11:15:22,364:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:22,514:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:22,515:INFO:Creating metrics dataframe +2023-11-09 11:15:22,526:INFO:Initializing Least Angle Regression +2023-11-09 11:15:22,526:INFO:Total runtime is 0.01861740748087565 minutes +2023-11-09 11:15:22,531:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:22,532:INFO:Initializing create_model() +2023-11-09 11:15:22,532:INFO:create_model(self=, estimator=lar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:22,532:INFO:Checking exceptions +2023-11-09 11:15:22,533:INFO:Importing libraries +2023-11-09 11:15:22,533:INFO:Copying training dataset +2023-11-09 11:15:22,540:INFO:Defining folds +2023-11-09 11:15:22,540:INFO:Declaring metric variables +2023-11-09 11:15:22,545:INFO:Importing untrained model +2023-11-09 11:15:22,549:INFO:Least Angle Regression Imported successfully +2023-11-09 11:15:22,555:INFO:Starting cross validation +2023-11-09 11:15:22,556:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:22,625:INFO:Calculating mean and std +2023-11-09 11:15:22,625:INFO:Creating metrics dataframe +2023-11-09 11:15:22,628:INFO:Uploading results into container +2023-11-09 11:15:22,629:INFO:Uploading model into container now +2023-11-09 11:15:22,629:INFO:_master_model_container: 5 +2023-11-09 11:15:22,629:INFO:_display_container: 2 +2023-11-09 11:15:22,629:INFO:Lars(random_state=123) +2023-11-09 11:15:22,630:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:22,749:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:22,749:INFO:Creating metrics dataframe +2023-11-09 11:15:22,757:INFO:Initializing Lasso Least Angle Regression +2023-11-09 11:15:22,757:INFO:Total runtime is 0.022479029496510823 minutes +2023-11-09 11:15:22,761:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:22,761:INFO:Initializing create_model() +2023-11-09 11:15:22,761:INFO:create_model(self=, estimator=llar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:22,761:INFO:Checking exceptions +2023-11-09 11:15:22,761:INFO:Importing libraries +2023-11-09 11:15:22,762:INFO:Copying training dataset +2023-11-09 11:15:22,765:INFO:Defining folds +2023-11-09 11:15:22,765:INFO:Declaring metric variables +2023-11-09 11:15:22,768:INFO:Importing untrained model +2023-11-09 11:15:22,772:INFO:Lasso Least Angle Regression Imported successfully +2023-11-09 11:15:22,778:INFO:Starting cross validation +2023-11-09 11:15:22,779:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:22,853:INFO:Calculating mean and std +2023-11-09 11:15:22,854:INFO:Creating metrics dataframe +2023-11-09 11:15:22,857:INFO:Uploading results into container +2023-11-09 11:15:22,857:INFO:Uploading model into container now +2023-11-09 11:15:22,857:INFO:_master_model_container: 6 +2023-11-09 11:15:22,857:INFO:_display_container: 2 +2023-11-09 11:15:22,858:INFO:LassoLars(random_state=123) +2023-11-09 11:15:22,858:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:22,990:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:22,990:INFO:Creating metrics dataframe +2023-11-09 11:15:22,999:INFO:Initializing Orthogonal Matching Pursuit +2023-11-09 11:15:22,999:INFO:Total runtime is 0.026512602965037026 minutes +2023-11-09 11:15:23,003:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:23,003:INFO:Initializing create_model() +2023-11-09 11:15:23,003:INFO:create_model(self=, estimator=omp, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:23,003:INFO:Checking exceptions +2023-11-09 11:15:23,003:INFO:Importing libraries +2023-11-09 11:15:23,003:INFO:Copying training dataset +2023-11-09 11:15:23,007:INFO:Defining folds +2023-11-09 11:15:23,008:INFO:Declaring metric variables +2023-11-09 11:15:23,011:INFO:Importing untrained model +2023-11-09 11:15:23,014:INFO:Orthogonal Matching Pursuit Imported successfully +2023-11-09 11:15:23,020:INFO:Starting cross validation +2023-11-09 11:15:23,021:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:23,103:INFO:Calculating mean and std +2023-11-09 11:15:23,104:INFO:Creating metrics dataframe +2023-11-09 11:15:23,108:INFO:Uploading results into container +2023-11-09 11:15:23,110:INFO:Uploading model into container now +2023-11-09 11:15:23,110:INFO:_master_model_container: 7 +2023-11-09 11:15:23,110:INFO:_display_container: 2 +2023-11-09 11:15:23,110:INFO:OrthogonalMatchingPursuit() +2023-11-09 11:15:23,110:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:23,240:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:23,241:INFO:Creating metrics dataframe +2023-11-09 11:15:23,249:INFO:Initializing Bayesian Ridge +2023-11-09 11:15:23,250:INFO:Total runtime is 0.030683565139770504 minutes +2023-11-09 11:15:23,253:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:23,254:INFO:Initializing create_model() +2023-11-09 11:15:23,254:INFO:create_model(self=, estimator=br, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:23,254:INFO:Checking exceptions +2023-11-09 11:15:23,254:INFO:Importing libraries +2023-11-09 11:15:23,254:INFO:Copying training dataset +2023-11-09 11:15:23,257:INFO:Defining folds +2023-11-09 11:15:23,257:INFO:Declaring metric variables +2023-11-09 11:15:23,260:INFO:Importing untrained model +2023-11-09 11:15:23,263:INFO:Bayesian Ridge Imported successfully +2023-11-09 11:15:23,269:INFO:Starting cross validation +2023-11-09 11:15:23,270:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:23,341:INFO:Calculating mean and std +2023-11-09 11:15:23,342:INFO:Creating metrics dataframe +2023-11-09 11:15:23,347:INFO:Uploading results into container +2023-11-09 11:15:23,347:INFO:Uploading model into container now +2023-11-09 11:15:23,348:INFO:_master_model_container: 8 +2023-11-09 11:15:23,348:INFO:_display_container: 2 +2023-11-09 11:15:23,348:INFO:BayesianRidge() +2023-11-09 11:15:23,348:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:23,473:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:23,473:INFO:Creating metrics dataframe +2023-11-09 11:15:23,483:INFO:Initializing Passive Aggressive Regressor +2023-11-09 11:15:23,483:INFO:Total runtime is 0.03457204500834147 minutes +2023-11-09 11:15:23,486:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:23,487:INFO:Initializing create_model() +2023-11-09 11:15:23,487:INFO:create_model(self=, estimator=par, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:23,487:INFO:Checking exceptions +2023-11-09 11:15:23,487:INFO:Importing libraries +2023-11-09 11:15:23,487:INFO:Copying training dataset +2023-11-09 11:15:23,491:INFO:Defining folds +2023-11-09 11:15:23,491:INFO:Declaring metric variables +2023-11-09 11:15:23,494:INFO:Importing untrained model +2023-11-09 11:15:23,498:INFO:Passive Aggressive Regressor Imported successfully +2023-11-09 11:15:23,503:INFO:Starting cross validation +2023-11-09 11:15:23,504:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:23,602:INFO:Calculating mean and std +2023-11-09 11:15:23,603:INFO:Creating metrics dataframe +2023-11-09 11:15:23,607:INFO:Uploading results into container +2023-11-09 11:15:23,608:INFO:Uploading model into container now +2023-11-09 11:15:23,608:INFO:_master_model_container: 9 +2023-11-09 11:15:23,608:INFO:_display_container: 2 +2023-11-09 11:15:23,609:INFO:PassiveAggressiveRegressor(random_state=123) +2023-11-09 11:15:23,609:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:23,742:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:23,742:INFO:Creating metrics dataframe +2023-11-09 11:15:23,755:INFO:Initializing Huber Regressor +2023-11-09 11:15:23,755:INFO:Total runtime is 0.039113608996073405 minutes +2023-11-09 11:15:23,759:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:23,759:INFO:Initializing create_model() +2023-11-09 11:15:23,759:INFO:create_model(self=, estimator=huber, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:23,760:INFO:Checking exceptions +2023-11-09 11:15:23,760:INFO:Importing libraries +2023-11-09 11:15:23,760:INFO:Copying training dataset +2023-11-09 11:15:23,764:INFO:Defining folds +2023-11-09 11:15:23,764:INFO:Declaring metric variables +2023-11-09 11:15:23,768:INFO:Importing untrained model +2023-11-09 11:15:23,772:INFO:Huber Regressor Imported successfully +2023-11-09 11:15:23,779:INFO:Starting cross validation +2023-11-09 11:15:23,780:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:23,927:INFO:Calculating mean and std +2023-11-09 11:15:23,929:INFO:Creating metrics dataframe +2023-11-09 11:15:23,933:INFO:Uploading results into container +2023-11-09 11:15:23,933:INFO:Uploading model into container now +2023-11-09 11:15:23,933:INFO:_master_model_container: 10 +2023-11-09 11:15:23,934:INFO:_display_container: 2 +2023-11-09 11:15:23,934:INFO:HuberRegressor() +2023-11-09 11:15:23,934:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:24,055:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:24,055:INFO:Creating metrics dataframe +2023-11-09 11:15:24,065:INFO:Initializing K Neighbors Regressor +2023-11-09 11:15:24,065:INFO:Total runtime is 0.04427545468012492 minutes +2023-11-09 11:15:24,069:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:24,070:INFO:Initializing create_model() +2023-11-09 11:15:24,070:INFO:create_model(self=, estimator=knn, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:24,070:INFO:Checking exceptions +2023-11-09 11:15:24,070:INFO:Importing libraries +2023-11-09 11:15:24,070:INFO:Copying training dataset +2023-11-09 11:15:24,075:INFO:Defining folds +2023-11-09 11:15:24,075:INFO:Declaring metric variables +2023-11-09 11:15:24,079:INFO:Importing untrained model +2023-11-09 11:15:24,082:INFO:K Neighbors Regressor Imported successfully +2023-11-09 11:15:24,088:INFO:Starting cross validation +2023-11-09 11:15:24,089:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:24,225:INFO:Calculating mean and std +2023-11-09 11:15:24,227:INFO:Creating metrics dataframe +2023-11-09 11:15:24,233:INFO:Uploading results into container +2023-11-09 11:15:24,234:INFO:Uploading model into container now +2023-11-09 11:15:24,235:INFO:_master_model_container: 11 +2023-11-09 11:15:24,235:INFO:_display_container: 2 +2023-11-09 11:15:24,236:INFO:KNeighborsRegressor(n_jobs=-1) +2023-11-09 11:15:24,236:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:24,368:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:24,368:INFO:Creating metrics dataframe +2023-11-09 11:15:24,377:INFO:Initializing Decision Tree Regressor +2023-11-09 11:15:24,377:INFO:Total runtime is 0.049476468563079835 minutes +2023-11-09 11:15:24,381:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:24,381:INFO:Initializing create_model() +2023-11-09 11:15:24,381:INFO:create_model(self=, estimator=dt, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:24,382:INFO:Checking exceptions +2023-11-09 11:15:24,382:INFO:Importing libraries +2023-11-09 11:15:24,382:INFO:Copying training dataset +2023-11-09 11:15:24,385:INFO:Defining folds +2023-11-09 11:15:24,385:INFO:Declaring metric variables +2023-11-09 11:15:24,388:INFO:Importing untrained model +2023-11-09 11:15:24,392:INFO:Decision Tree Regressor Imported successfully +2023-11-09 11:15:24,397:INFO:Starting cross validation +2023-11-09 11:15:24,398:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:24,469:INFO:Calculating mean and std +2023-11-09 11:15:24,470:INFO:Creating metrics dataframe +2023-11-09 11:15:24,472:INFO:Uploading results into container +2023-11-09 11:15:24,473:INFO:Uploading model into container now +2023-11-09 11:15:24,473:INFO:_master_model_container: 12 +2023-11-09 11:15:24,473:INFO:_display_container: 2 +2023-11-09 11:15:24,473:INFO:DecisionTreeRegressor(random_state=123) +2023-11-09 11:15:24,473:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:24,597:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:24,598:INFO:Creating metrics dataframe +2023-11-09 11:15:24,610:INFO:Initializing Random Forest Regressor +2023-11-09 11:15:24,610:INFO:Total runtime is 0.05335224469502767 minutes +2023-11-09 11:15:24,614:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:24,614:INFO:Initializing create_model() +2023-11-09 11:15:24,615:INFO:create_model(self=, estimator=rf, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:24,615:INFO:Checking exceptions +2023-11-09 11:15:24,615:INFO:Importing libraries +2023-11-09 11:15:24,615:INFO:Copying training dataset +2023-11-09 11:15:24,618:INFO:Defining folds +2023-11-09 11:15:24,618:INFO:Declaring metric variables +2023-11-09 11:15:24,622:INFO:Importing untrained model +2023-11-09 11:15:24,625:INFO:Random Forest Regressor Imported successfully +2023-11-09 11:15:24,631:INFO:Starting cross validation +2023-11-09 11:15:24,632:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:25,090:INFO:Calculating mean and std +2023-11-09 11:15:25,092:INFO:Creating metrics dataframe +2023-11-09 11:15:25,095:INFO:Uploading results into container +2023-11-09 11:15:25,096:INFO:Uploading model into container now +2023-11-09 11:15:25,096:INFO:_master_model_container: 13 +2023-11-09 11:15:25,096:INFO:_display_container: 2 +2023-11-09 11:15:25,097:INFO:RandomForestRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:15:25,097:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:25,215:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:25,216:INFO:Creating metrics dataframe +2023-11-09 11:15:25,229:INFO:Initializing Extra Trees Regressor +2023-11-09 11:15:25,229:INFO:Total runtime is 0.06367428302764892 minutes +2023-11-09 11:15:25,233:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:25,233:INFO:Initializing create_model() +2023-11-09 11:15:25,233:INFO:create_model(self=, estimator=et, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:25,233:INFO:Checking exceptions +2023-11-09 11:15:25,233:INFO:Importing libraries +2023-11-09 11:15:25,233:INFO:Copying training dataset +2023-11-09 11:15:25,238:INFO:Defining folds +2023-11-09 11:15:25,238:INFO:Declaring metric variables +2023-11-09 11:15:25,242:INFO:Importing untrained model +2023-11-09 11:15:25,246:INFO:Extra Trees Regressor Imported successfully +2023-11-09 11:15:25,252:INFO:Starting cross validation +2023-11-09 11:15:25,254:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:25,576:INFO:Calculating mean and std +2023-11-09 11:15:25,577:INFO:Creating metrics dataframe +2023-11-09 11:15:25,581:INFO:Uploading results into container +2023-11-09 11:15:25,582:INFO:Uploading model into container now +2023-11-09 11:15:25,582:INFO:_master_model_container: 14 +2023-11-09 11:15:25,582:INFO:_display_container: 2 +2023-11-09 11:15:25,583:INFO:ExtraTreesRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:15:25,583:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:25,698:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:25,698:INFO:Creating metrics dataframe +2023-11-09 11:15:25,708:INFO:Initializing AdaBoost Regressor +2023-11-09 11:15:25,708:INFO:Total runtime is 0.07165770530700684 minutes +2023-11-09 11:15:25,712:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:25,712:INFO:Initializing create_model() +2023-11-09 11:15:25,712:INFO:create_model(self=, estimator=ada, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:25,712:INFO:Checking exceptions +2023-11-09 11:15:25,712:INFO:Importing libraries +2023-11-09 11:15:25,712:INFO:Copying training dataset +2023-11-09 11:15:25,716:INFO:Defining folds +2023-11-09 11:15:25,717:INFO:Declaring metric variables +2023-11-09 11:15:25,720:INFO:Importing untrained model +2023-11-09 11:15:25,723:INFO:AdaBoost Regressor Imported successfully +2023-11-09 11:15:25,729:INFO:Starting cross validation +2023-11-09 11:15:25,730:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:25,922:INFO:Calculating mean and std +2023-11-09 11:15:25,923:INFO:Creating metrics dataframe +2023-11-09 11:15:25,927:INFO:Uploading results into container +2023-11-09 11:15:25,928:INFO:Uploading model into container now +2023-11-09 11:15:25,928:INFO:_master_model_container: 15 +2023-11-09 11:15:25,928:INFO:_display_container: 2 +2023-11-09 11:15:25,929:INFO:AdaBoostRegressor(random_state=123) +2023-11-09 11:15:25,929:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:26,046:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:26,046:INFO:Creating metrics dataframe +2023-11-09 11:15:26,057:INFO:Initializing Gradient Boosting Regressor +2023-11-09 11:15:26,057:INFO:Total runtime is 0.07747397820154826 minutes +2023-11-09 11:15:26,061:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:26,061:INFO:Initializing create_model() +2023-11-09 11:15:26,061:INFO:create_model(self=, estimator=gbr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:26,061:INFO:Checking exceptions +2023-11-09 11:15:26,062:INFO:Importing libraries +2023-11-09 11:15:26,062:INFO:Copying training dataset +2023-11-09 11:15:26,065:INFO:Defining folds +2023-11-09 11:15:26,065:INFO:Declaring metric variables +2023-11-09 11:15:26,068:INFO:Importing untrained model +2023-11-09 11:15:26,072:INFO:Gradient Boosting Regressor Imported successfully +2023-11-09 11:15:26,078:INFO:Starting cross validation +2023-11-09 11:15:26,079:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:26,234:INFO:Calculating mean and std +2023-11-09 11:15:26,235:INFO:Creating metrics dataframe +2023-11-09 11:15:26,239:INFO:Uploading results into container +2023-11-09 11:15:26,240:INFO:Uploading model into container now +2023-11-09 11:15:26,240:INFO:_master_model_container: 16 +2023-11-09 11:15:26,240:INFO:_display_container: 2 +2023-11-09 11:15:26,241:INFO:GradientBoostingRegressor(random_state=123) +2023-11-09 11:15:26,241:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:26,405:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:26,405:INFO:Creating metrics dataframe +2023-11-09 11:15:26,417:INFO:Initializing Light Gradient Boosting Machine +2023-11-09 11:15:26,418:INFO:Total runtime is 0.08348162174224855 minutes +2023-11-09 11:15:26,421:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:26,421:INFO:Initializing create_model() +2023-11-09 11:15:26,422:INFO:create_model(self=, estimator=lightgbm, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:26,422:INFO:Checking exceptions +2023-11-09 11:15:26,422:INFO:Importing libraries +2023-11-09 11:15:26,422:INFO:Copying training dataset +2023-11-09 11:15:26,425:INFO:Defining folds +2023-11-09 11:15:26,426:INFO:Declaring metric variables +2023-11-09 11:15:26,430:INFO:Importing untrained model +2023-11-09 11:15:26,434:INFO:Light Gradient Boosting Machine Imported successfully +2023-11-09 11:15:26,439:INFO:Starting cross validation +2023-11-09 11:15:26,440:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:27,964:INFO:Calculating mean and std +2023-11-09 11:15:27,965:INFO:Creating metrics dataframe +2023-11-09 11:15:27,968:INFO:Uploading results into container +2023-11-09 11:15:27,969:INFO:Uploading model into container now +2023-11-09 11:15:27,969:INFO:_master_model_container: 17 +2023-11-09 11:15:27,970:INFO:_display_container: 2 +2023-11-09 11:15:27,970:INFO:LGBMRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:15:27,970:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:28,099:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:28,099:INFO:Creating metrics dataframe +2023-11-09 11:15:28,111:INFO:Initializing Dummy Regressor +2023-11-09 11:15:28,112:INFO:Total runtime is 0.11171794732411704 minutes +2023-11-09 11:15:28,116:INFO:SubProcess create_model() called ================================== +2023-11-09 11:15:28,116:INFO:Initializing create_model() +2023-11-09 11:15:28,116:INFO:create_model(self=, estimator=dummy, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:28,116:INFO:Checking exceptions +2023-11-09 11:15:28,116:INFO:Importing libraries +2023-11-09 11:15:28,116:INFO:Copying training dataset +2023-11-09 11:15:28,120:INFO:Defining folds +2023-11-09 11:15:28,121:INFO:Declaring metric variables +2023-11-09 11:15:28,124:INFO:Importing untrained model +2023-11-09 11:15:28,127:INFO:Dummy Regressor Imported successfully +2023-11-09 11:15:28,133:INFO:Starting cross validation +2023-11-09 11:15:28,134:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:15:28,200:INFO:Calculating mean and std +2023-11-09 11:15:28,200:INFO:Creating metrics dataframe +2023-11-09 11:15:28,204:INFO:Uploading results into container +2023-11-09 11:15:28,204:INFO:Uploading model into container now +2023-11-09 11:15:28,205:INFO:_master_model_container: 18 +2023-11-09 11:15:28,205:INFO:_display_container: 2 +2023-11-09 11:15:28,205:INFO:DummyRegressor() +2023-11-09 11:15:28,205:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:28,332:INFO:SubProcess create_model() end ================================== +2023-11-09 11:15:28,332:INFO:Creating metrics dataframe +2023-11-09 11:15:28,353:INFO:Initializing create_model() +2023-11-09 11:15:28,353:INFO:create_model(self=, estimator=HuberRegressor(), fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=False, predict=False, fit_kwargs={}, groups=None, refit=True, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=None, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:15:28,353:INFO:Checking exceptions +2023-11-09 11:15:28,354:INFO:Importing libraries +2023-11-09 11:15:28,354:INFO:Copying training dataset +2023-11-09 11:15:28,358:INFO:Defining folds +2023-11-09 11:15:28,358:INFO:Declaring metric variables +2023-11-09 11:15:28,358:INFO:Importing untrained model +2023-11-09 11:15:28,358:INFO:Declaring custom model +2023-11-09 11:15:28,358:INFO:Huber Regressor Imported successfully +2023-11-09 11:15:28,359:INFO:Cross validation set to False +2023-11-09 11:15:28,359:INFO:Fitting Model +2023-11-09 11:15:28,388:INFO:HuberRegressor() +2023-11-09 11:15:28,388:INFO:create_model() successfully completed...................................... +2023-11-09 11:15:28,591:INFO:_master_model_container: 18 +2023-11-09 11:15:28,591:INFO:_display_container: 2 +2023-11-09 11:15:28,591:INFO:HuberRegressor() +2023-11-09 11:15:28,591:INFO:compare_models() successfully completed...................................... +2023-11-09 11:15:28,733:INFO:Initializing predict_model() +2023-11-09 11:15:28,734:INFO:predict_model(self=, estimator=HuberRegressor(), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=.encode_labels at 0x7fbb2cb1bca0>) +2023-11-09 11:15:28,735:INFO:Checking exceptions +2023-11-09 11:15:28,735:INFO:Preloading libraries +2023-11-09 11:15:28,737:INFO:Set up data. +2023-11-09 11:15:28,740:INFO:Set up index. +2023-11-09 11:15:29,109:WARNING:/tmp/ipykernel_54540/2181003279.py:1: SettingWithCopyWarning: + + +A value is trying to be set on a copy of a slice from a DataFrame + +See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy + + +2023-11-09 11:16:24,458:INFO:Initializing predict_model() +2023-11-09 11:16:24,460:INFO:predict_model(self=, estimator=HuberRegressor(), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=.encode_labels at 0x7fbb2cc74790>) +2023-11-09 11:16:24,460:INFO:Checking exceptions +2023-11-09 11:16:24,460:INFO:Preloading libraries +2023-11-09 11:16:24,463:INFO:Set up data. +2023-11-09 11:16:24,466:INFO:Set up index. +2023-11-09 11:19:48,927:WARNING:/tmp/ipykernel_54540/2181003279.py:1: SettingWithCopyWarning: + + +A value is trying to be set on a copy of a slice from a DataFrame + +See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy + + +2023-11-09 11:21:05,437:WARNING:/tmp/ipykernel_54540/716735288.py:1: SettingWithCopyWarning: + + +A value is trying to be set on a copy of a slice from a DataFrame + +See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy + + +2023-11-09 11:21:20,020:WARNING:/tmp/ipykernel_54540/4098162356.py:1: SettingWithCopyWarning: + + +A value is trying to be set on a copy of a slice from a DataFrame + +See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy + + +2023-11-09 11:21:23,313:INFO:PyCaret RegressionExperiment +2023-11-09 11:21:23,313:INFO:Logging name: reg-default-name +2023-11-09 11:21:23,313:INFO:ML Usecase: MLUsecase.REGRESSION +2023-11-09 11:21:23,313:INFO:version 3.1.0 +2023-11-09 11:21:23,313:INFO:Initializing setup() +2023-11-09 11:21:23,313:INFO:self.USI: 4f24 +2023-11-09 11:21:23,314:INFO:self._variable_keys: {'seed', 'idx', 'transform_target_param', 'gpu_param', 'target_param', 'log_plots_param', 'pipeline', 'logging_param', 'fold_groups_param', '_ml_usecase', 'html_param', 'gpu_n_jobs_param', 'y', 'y_test', 'y_train', 'memory', 'exp_id', 'X_test', 'exp_name_log', 'USI', 'data', 'X_train', 'fold_shuffle_param', 'X', 'fold_generator', 'n_jobs_param', '_available_plots'} +2023-11-09 11:21:23,314:INFO:Checking environment +2023-11-09 11:21:23,314:INFO:python_version: 3.8.18 +2023-11-09 11:21:23,314:INFO:python_build: ('default', 'Sep 11 2023 13:40:15') +2023-11-09 11:21:23,314:INFO:machine: x86_64 +2023-11-09 11:21:23,315:INFO:platform: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:21:23,315:INFO:Memory: svmem(total=8315187200, available=4807208960, percent=42.2, used=3173343232, free=459407360, active=1474170880, inactive=5536223232, buffers=337453056, cached=4344983552, shared=4476928, slab=650760192) +2023-11-09 11:21:23,315:INFO:Physical Core: 1 +2023-11-09 11:21:23,316:INFO:Logical Core: 2 +2023-11-09 11:21:23,316:INFO:Checking libraries +2023-11-09 11:21:23,316:INFO:System: +2023-11-09 11:21:23,316:INFO: python: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] +2023-11-09 11:21:23,316:INFO:executable: /workspaces/D2I-Jupyter-Notebook-Tools/.conda/bin/python +2023-11-09 11:21:23,316:INFO: machine: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:21:23,316:INFO:PyCaret required dependencies: +2023-11-09 11:21:23,316:INFO: pip: 23.3 +2023-11-09 11:21:23,316:INFO: setuptools: 68.0.0 +2023-11-09 11:21:23,316:INFO: pycaret: 3.1.0 +2023-11-09 11:21:23,316:INFO: IPython: 8.12.0 +2023-11-09 11:21:23,316:INFO: ipywidgets: 8.1.1 +2023-11-09 11:21:23,316:INFO: tqdm: 4.66.1 +2023-11-09 11:21:23,316:INFO: numpy: 1.23.5 +2023-11-09 11:21:23,316:INFO: pandas: 1.5.3 +2023-11-09 11:21:23,317:INFO: jinja2: 3.1.2 +2023-11-09 11:21:23,317:INFO: scipy: 1.10.1 +2023-11-09 11:21:23,317:INFO: joblib: 1.3.2 +2023-11-09 11:21:23,317:INFO: sklearn: 1.2.2 +2023-11-09 11:21:23,317:INFO: pyod: 1.1.1 +2023-11-09 11:21:23,317:INFO: imblearn: 0.11.0 +2023-11-09 11:21:23,317:INFO: category_encoders: 2.6.3 +2023-11-09 11:21:23,317:INFO: lightgbm: 4.1.0 +2023-11-09 11:21:23,317:INFO: numba: 0.58.1 +2023-11-09 11:21:23,317:INFO: requests: 2.31.0 +2023-11-09 11:21:23,317:INFO: matplotlib: 3.7.3 +2023-11-09 11:21:23,317:INFO: scikitplot: 0.3.7 +2023-11-09 11:21:23,317:INFO: yellowbrick: 1.5 +2023-11-09 11:21:23,317:INFO: plotly: 5.18.0 +2023-11-09 11:21:23,317:INFO: plotly-resampler: Not installed +2023-11-09 11:21:23,317:INFO: kaleido: 0.2.1 +2023-11-09 11:21:23,317:INFO: schemdraw: 0.15 +2023-11-09 11:21:23,317:INFO: statsmodels: 0.14.0 +2023-11-09 11:21:23,317:INFO: sktime: 0.21.1 +2023-11-09 11:21:23,317:INFO: tbats: 1.1.3 +2023-11-09 11:21:23,317:INFO: pmdarima: 2.0.4 +2023-11-09 11:21:23,318:INFO: psutil: 5.9.0 +2023-11-09 11:21:23,318:INFO: markupsafe: 2.1.3 +2023-11-09 11:21:23,318:INFO: pickle5: Not installed +2023-11-09 11:21:23,318:INFO: cloudpickle: 3.0.0 +2023-11-09 11:21:23,318:INFO: deprecation: 2.1.0 +2023-11-09 11:21:23,318:INFO: xxhash: 3.4.1 +2023-11-09 11:21:23,318:INFO: wurlitzer: 3.0.3 +2023-11-09 11:21:23,318:INFO:PyCaret optional dependencies: +2023-11-09 11:21:23,318:INFO: shap: Not installed +2023-11-09 11:21:23,318:INFO: interpret: Not installed +2023-11-09 11:21:23,318:INFO: umap: Not installed +2023-11-09 11:21:23,318:INFO: ydata_profiling: Not installed +2023-11-09 11:21:23,318:INFO: explainerdashboard: Not installed +2023-11-09 11:21:23,318:INFO: autoviz: Not installed +2023-11-09 11:21:23,318:INFO: fairlearn: Not installed +2023-11-09 11:21:23,318:INFO: deepchecks: Not installed +2023-11-09 11:21:23,318:INFO: xgboost: Not installed +2023-11-09 11:21:23,318:INFO: catboost: Not installed +2023-11-09 11:21:23,319:INFO: kmodes: Not installed +2023-11-09 11:21:23,319:INFO: mlxtend: Not installed +2023-11-09 11:21:23,319:INFO: statsforecast: Not installed +2023-11-09 11:21:23,319:INFO: tune_sklearn: Not installed +2023-11-09 11:21:23,319:INFO: ray: Not installed +2023-11-09 11:21:23,319:INFO: hyperopt: Not installed +2023-11-09 11:21:23,319:INFO: optuna: Not installed +2023-11-09 11:21:23,319:INFO: skopt: Not installed +2023-11-09 11:21:23,319:INFO: mlflow: Not installed +2023-11-09 11:21:23,319:INFO: gradio: Not installed +2023-11-09 11:21:23,319:INFO: fastapi: Not installed +2023-11-09 11:21:23,319:INFO: uvicorn: Not installed +2023-11-09 11:21:23,319:INFO: m2cgen: Not installed +2023-11-09 11:21:23,319:INFO: evidently: Not installed +2023-11-09 11:21:23,319:INFO: fugue: Not installed +2023-11-09 11:21:23,319:INFO: streamlit: Not installed +2023-11-09 11:21:23,319:INFO: prophet: Not installed +2023-11-09 11:21:23,319:INFO:None +2023-11-09 11:21:23,319:INFO:Set up data. +2023-11-09 11:21:23,323:INFO:Set up folding strategy. +2023-11-09 11:21:23,323:INFO:Set up train/test split. +2023-11-09 11:21:23,323:INFO:Set up data. +2023-11-09 11:21:23,327:INFO:Set up index. +2023-11-09 11:21:23,327:INFO:Assigning column types. +2023-11-09 11:21:23,329:INFO:Engine successfully changes for model 'lr' to 'sklearn'. +2023-11-09 11:21:23,330:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,335:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,339:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,394:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,436:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,437:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:23,437:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:23,438:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,442:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,446:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,493:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,530:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,531:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:23,531:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:23,532:INFO:Engine successfully changes for model 'lasso' to 'sklearn'. +2023-11-09 11:21:23,536:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,539:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,587:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,625:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,626:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:23,626:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:23,630:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,634:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,682:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,721:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,721:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:23,722:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:23,722:INFO:Engine successfully changes for model 'ridge' to 'sklearn'. +2023-11-09 11:21:23,730:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,777:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,815:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,815:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:23,815:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:23,823:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,870:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,907:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:21:23,908:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:23,908:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:23,908:INFO:Engine successfully changes for model 'en' to 'sklearn'. +2023-11-09 11:21:23,964:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:21:24,002:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:21:24,003:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:24,003:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:24,069:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:21:24,142:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:21:24,143:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:24,143:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:24,144:INFO:Engine successfully changes for model 'knn' to 'sklearn'. +2023-11-09 11:21:24,248:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:21:24,285:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:24,286:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:24,346:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:21:24,415:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:24,416:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:24,416:INFO:Engine successfully changes for model 'svm' to 'sklearn'. +2023-11-09 11:21:24,596:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:24,596:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:24,707:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:24,707:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:24,708:INFO:Preparing preprocessing pipeline... +2023-11-09 11:21:24,708:INFO:Set up target transformation. +2023-11-09 11:21:24,708:INFO:Set up simple imputation. +2023-11-09 11:21:24,709:INFO:Set up column name cleaning. +2023-11-09 11:21:24,735:INFO:Finished creating preprocessing pipeline. +2023-11-09 11:21:24,741:INFO:Pipeline: Pipeline(memory=FastMemory(location=/tmp/joblib), + steps=[('target_transformation', + TransformerWrapperWithInverse(transformer=TargetTransformer(estimator=PowerTransformer(standardize=False)))), + ('numerical_imputer', + TransformerWrapper(include=['Year', 'Series'], + transformer=SimpleImputer())), + ('categorical_imputer', + TransformerWrapper(include=[], + transformer=SimpleImputer(strategy='most_frequent'))), + ('clean_column_names', + TransformerWrapper(transformer=CleanColumnNames()))]) +2023-11-09 11:21:24,741:INFO:Creating final display dataframe. +2023-11-09 11:21:24,818:INFO:Setup _display_container: Description Value +0 Session id 123 +1 Target Average price All property types +2 Target type Regression +3 Original data shape (523, 4) +4 Transformed data shape (523, 4) +5 Transformed train set shape (372, 4) +6 Transformed test set shape (151, 4) +7 Numeric features 2 +8 Preprocess True +9 Imputation type simple +10 Numeric imputation mean +11 Categorical imputation mode +12 Transform target True +13 Transform target method yeo-johnson +14 Fold Generator TimeSeriesSplit +15 Fold Number 3 +16 CPU Jobs -1 +17 Use GPU False +18 Log Experiment False +19 Experiment Name reg-default-name +20 USI 4f24 +2023-11-09 11:21:24,923:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:24,923:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:25,022:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:25,022:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:21:25,023:INFO:setup() successfully completed in 1.71s............... +2023-11-09 11:21:25,114:INFO:Initializing compare_models() +2023-11-09 11:21:25,114:INFO:compare_models(self=, include=None, fold=None, round=4, cross_validation=True, sort=MAE, n_select=1, budget_time=None, turbo=True, errors=ignore, fit_kwargs=None, groups=None, experiment_custom_tags=None, probability_threshold=None, verbose=True, parallel=None, caller_params={'self': , 'include': None, 'exclude': None, 'fold': None, 'round': 4, 'cross_validation': True, 'sort': 'MAE', 'n_select': 1, 'budget_time': None, 'turbo': True, 'errors': 'ignore', 'fit_kwargs': None, 'groups': None, 'experiment_custom_tags': None, 'engine': None, 'verbose': True, 'parallel': None, '__class__': }, exclude=None) +2023-11-09 11:21:25,114:INFO:Checking exceptions +2023-11-09 11:21:25,117:INFO:Preparing display monitor +2023-11-09 11:21:25,155:INFO:Initializing Linear Regression +2023-11-09 11:21:25,155:INFO:Total runtime is 5.054473876953125e-06 minutes +2023-11-09 11:21:25,158:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:25,159:INFO:Initializing create_model() +2023-11-09 11:21:25,159:INFO:create_model(self=, estimator=lr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:25,159:INFO:Checking exceptions +2023-11-09 11:21:25,159:INFO:Importing libraries +2023-11-09 11:21:25,160:INFO:Copying training dataset +2023-11-09 11:21:25,163:INFO:Defining folds +2023-11-09 11:21:25,163:INFO:Declaring metric variables +2023-11-09 11:21:25,166:INFO:Importing untrained model +2023-11-09 11:21:25,170:INFO:Linear Regression Imported successfully +2023-11-09 11:21:25,179:INFO:Starting cross validation +2023-11-09 11:21:25,180:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:27,376:INFO:Calculating mean and std +2023-11-09 11:21:27,378:INFO:Creating metrics dataframe +2023-11-09 11:21:27,382:INFO:Uploading results into container +2023-11-09 11:21:27,383:INFO:Uploading model into container now +2023-11-09 11:21:27,384:INFO:_master_model_container: 1 +2023-11-09 11:21:27,384:INFO:_display_container: 2 +2023-11-09 11:21:27,384:INFO:LinearRegression(n_jobs=-1) +2023-11-09 11:21:27,384:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:27,535:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:27,536:INFO:Creating metrics dataframe +2023-11-09 11:21:27,544:INFO:Initializing Lasso Regression +2023-11-09 11:21:27,544:INFO:Total runtime is 0.03981637159983317 minutes +2023-11-09 11:21:27,548:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:27,548:INFO:Initializing create_model() +2023-11-09 11:21:27,548:INFO:create_model(self=, estimator=lasso, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:27,548:INFO:Checking exceptions +2023-11-09 11:21:27,549:INFO:Importing libraries +2023-11-09 11:21:27,549:INFO:Copying training dataset +2023-11-09 11:21:27,552:INFO:Defining folds +2023-11-09 11:21:27,553:INFO:Declaring metric variables +2023-11-09 11:21:27,556:INFO:Importing untrained model +2023-11-09 11:21:27,560:INFO:Lasso Regression Imported successfully +2023-11-09 11:21:27,565:INFO:Starting cross validation +2023-11-09 11:21:27,566:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:27,643:INFO:Calculating mean and std +2023-11-09 11:21:27,644:INFO:Creating metrics dataframe +2023-11-09 11:21:27,647:INFO:Uploading results into container +2023-11-09 11:21:27,647:INFO:Uploading model into container now +2023-11-09 11:21:27,648:INFO:_master_model_container: 2 +2023-11-09 11:21:27,648:INFO:_display_container: 2 +2023-11-09 11:21:27,648:INFO:Lasso(random_state=123) +2023-11-09 11:21:27,648:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:27,769:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:27,769:INFO:Creating metrics dataframe +2023-11-09 11:21:27,778:INFO:Initializing Ridge Regression +2023-11-09 11:21:27,778:INFO:Total runtime is 0.04372069835662842 minutes +2023-11-09 11:21:27,781:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:27,782:INFO:Initializing create_model() +2023-11-09 11:21:27,782:INFO:create_model(self=, estimator=ridge, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:27,782:INFO:Checking exceptions +2023-11-09 11:21:27,783:INFO:Importing libraries +2023-11-09 11:21:27,783:INFO:Copying training dataset +2023-11-09 11:21:27,786:INFO:Defining folds +2023-11-09 11:21:27,786:INFO:Declaring metric variables +2023-11-09 11:21:27,789:INFO:Importing untrained model +2023-11-09 11:21:27,792:INFO:Ridge Regression Imported successfully +2023-11-09 11:21:27,798:INFO:Starting cross validation +2023-11-09 11:21:27,799:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:27,879:INFO:Calculating mean and std +2023-11-09 11:21:27,880:INFO:Creating metrics dataframe +2023-11-09 11:21:27,882:INFO:Uploading results into container +2023-11-09 11:21:27,883:INFO:Uploading model into container now +2023-11-09 11:21:27,883:INFO:_master_model_container: 3 +2023-11-09 11:21:27,883:INFO:_display_container: 2 +2023-11-09 11:21:27,884:INFO:Ridge(random_state=123) +2023-11-09 11:21:27,884:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:28,011:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:28,011:INFO:Creating metrics dataframe +2023-11-09 11:21:28,019:INFO:Initializing Elastic Net +2023-11-09 11:21:28,019:INFO:Total runtime is 0.0477394978205363 minutes +2023-11-09 11:21:28,023:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:28,024:INFO:Initializing create_model() +2023-11-09 11:21:28,024:INFO:create_model(self=, estimator=en, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:28,024:INFO:Checking exceptions +2023-11-09 11:21:28,024:INFO:Importing libraries +2023-11-09 11:21:28,024:INFO:Copying training dataset +2023-11-09 11:21:28,028:INFO:Defining folds +2023-11-09 11:21:28,028:INFO:Declaring metric variables +2023-11-09 11:21:28,031:INFO:Importing untrained model +2023-11-09 11:21:28,034:INFO:Elastic Net Imported successfully +2023-11-09 11:21:28,040:INFO:Starting cross validation +2023-11-09 11:21:28,042:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:28,119:INFO:Calculating mean and std +2023-11-09 11:21:28,120:INFO:Creating metrics dataframe +2023-11-09 11:21:28,123:INFO:Uploading results into container +2023-11-09 11:21:28,123:INFO:Uploading model into container now +2023-11-09 11:21:28,124:INFO:_master_model_container: 4 +2023-11-09 11:21:28,124:INFO:_display_container: 2 +2023-11-09 11:21:28,124:INFO:ElasticNet(random_state=123) +2023-11-09 11:21:28,124:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:28,257:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:28,257:INFO:Creating metrics dataframe +2023-11-09 11:21:28,265:INFO:Initializing Least Angle Regression +2023-11-09 11:21:28,265:INFO:Total runtime is 0.051840678850809736 minutes +2023-11-09 11:21:28,269:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:28,269:INFO:Initializing create_model() +2023-11-09 11:21:28,270:INFO:create_model(self=, estimator=lar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:28,270:INFO:Checking exceptions +2023-11-09 11:21:28,270:INFO:Importing libraries +2023-11-09 11:21:28,270:INFO:Copying training dataset +2023-11-09 11:21:28,273:INFO:Defining folds +2023-11-09 11:21:28,274:INFO:Declaring metric variables +2023-11-09 11:21:28,277:INFO:Importing untrained model +2023-11-09 11:21:28,280:INFO:Least Angle Regression Imported successfully +2023-11-09 11:21:28,286:INFO:Starting cross validation +2023-11-09 11:21:28,288:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:28,367:INFO:Calculating mean and std +2023-11-09 11:21:28,368:INFO:Creating metrics dataframe +2023-11-09 11:21:28,370:INFO:Uploading results into container +2023-11-09 11:21:28,371:INFO:Uploading model into container now +2023-11-09 11:21:28,371:INFO:_master_model_container: 5 +2023-11-09 11:21:28,371:INFO:_display_container: 2 +2023-11-09 11:21:28,372:INFO:Lars(random_state=123) +2023-11-09 11:21:28,372:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:28,508:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:28,508:INFO:Creating metrics dataframe +2023-11-09 11:21:28,520:INFO:Initializing Lasso Least Angle Regression +2023-11-09 11:21:28,521:INFO:Total runtime is 0.05610386927922567 minutes +2023-11-09 11:21:28,526:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:28,527:INFO:Initializing create_model() +2023-11-09 11:21:28,527:INFO:create_model(self=, estimator=llar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:28,527:INFO:Checking exceptions +2023-11-09 11:21:28,527:INFO:Importing libraries +2023-11-09 11:21:28,528:INFO:Copying training dataset +2023-11-09 11:21:28,533:INFO:Defining folds +2023-11-09 11:21:28,533:INFO:Declaring metric variables +2023-11-09 11:21:28,539:INFO:Importing untrained model +2023-11-09 11:21:28,545:INFO:Lasso Least Angle Regression Imported successfully +2023-11-09 11:21:28,553:INFO:Starting cross validation +2023-11-09 11:21:28,554:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:28,673:INFO:Calculating mean and std +2023-11-09 11:21:28,675:INFO:Creating metrics dataframe +2023-11-09 11:21:28,681:INFO:Uploading results into container +2023-11-09 11:21:28,682:INFO:Uploading model into container now +2023-11-09 11:21:28,682:INFO:_master_model_container: 6 +2023-11-09 11:21:28,682:INFO:_display_container: 2 +2023-11-09 11:21:28,683:INFO:LassoLars(random_state=123) +2023-11-09 11:21:28,683:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:28,840:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:28,840:INFO:Creating metrics dataframe +2023-11-09 11:21:28,853:INFO:Initializing Orthogonal Matching Pursuit +2023-11-09 11:21:28,853:INFO:Total runtime is 0.06163575251897176 minutes +2023-11-09 11:21:28,856:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:28,857:INFO:Initializing create_model() +2023-11-09 11:21:28,857:INFO:create_model(self=, estimator=omp, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:28,857:INFO:Checking exceptions +2023-11-09 11:21:28,857:INFO:Importing libraries +2023-11-09 11:21:28,857:INFO:Copying training dataset +2023-11-09 11:21:28,861:INFO:Defining folds +2023-11-09 11:21:28,862:INFO:Declaring metric variables +2023-11-09 11:21:28,865:INFO:Importing untrained model +2023-11-09 11:21:28,868:INFO:Orthogonal Matching Pursuit Imported successfully +2023-11-09 11:21:28,874:INFO:Starting cross validation +2023-11-09 11:21:28,875:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:28,963:INFO:Calculating mean and std +2023-11-09 11:21:28,964:INFO:Creating metrics dataframe +2023-11-09 11:21:28,968:INFO:Uploading results into container +2023-11-09 11:21:28,969:INFO:Uploading model into container now +2023-11-09 11:21:28,969:INFO:_master_model_container: 7 +2023-11-09 11:21:28,969:INFO:_display_container: 2 +2023-11-09 11:21:28,970:INFO:OrthogonalMatchingPursuit() +2023-11-09 11:21:28,970:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:29,100:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:29,100:INFO:Creating metrics dataframe +2023-11-09 11:21:29,109:INFO:Initializing Bayesian Ridge +2023-11-09 11:21:29,109:INFO:Total runtime is 0.06590712865193685 minutes +2023-11-09 11:21:29,113:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:29,113:INFO:Initializing create_model() +2023-11-09 11:21:29,113:INFO:create_model(self=, estimator=br, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:29,113:INFO:Checking exceptions +2023-11-09 11:21:29,113:INFO:Importing libraries +2023-11-09 11:21:29,113:INFO:Copying training dataset +2023-11-09 11:21:29,117:INFO:Defining folds +2023-11-09 11:21:29,117:INFO:Declaring metric variables +2023-11-09 11:21:29,121:INFO:Importing untrained model +2023-11-09 11:21:29,124:INFO:Bayesian Ridge Imported successfully +2023-11-09 11:21:29,130:INFO:Starting cross validation +2023-11-09 11:21:29,131:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:29,215:INFO:Calculating mean and std +2023-11-09 11:21:29,216:INFO:Creating metrics dataframe +2023-11-09 11:21:29,219:INFO:Uploading results into container +2023-11-09 11:21:29,220:INFO:Uploading model into container now +2023-11-09 11:21:29,221:INFO:_master_model_container: 8 +2023-11-09 11:21:29,221:INFO:_display_container: 2 +2023-11-09 11:21:29,221:INFO:BayesianRidge() +2023-11-09 11:21:29,221:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:29,391:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:29,391:INFO:Creating metrics dataframe +2023-11-09 11:21:29,401:INFO:Initializing Passive Aggressive Regressor +2023-11-09 11:21:29,402:INFO:Total runtime is 0.07077778577804565 minutes +2023-11-09 11:21:29,405:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:29,406:INFO:Initializing create_model() +2023-11-09 11:21:29,406:INFO:create_model(self=, estimator=par, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:29,406:INFO:Checking exceptions +2023-11-09 11:21:29,406:INFO:Importing libraries +2023-11-09 11:21:29,406:INFO:Copying training dataset +2023-11-09 11:21:29,409:INFO:Defining folds +2023-11-09 11:21:29,410:INFO:Declaring metric variables +2023-11-09 11:21:29,412:INFO:Importing untrained model +2023-11-09 11:21:29,416:INFO:Passive Aggressive Regressor Imported successfully +2023-11-09 11:21:29,423:INFO:Starting cross validation +2023-11-09 11:21:29,424:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:29,510:INFO:Calculating mean and std +2023-11-09 11:21:29,510:INFO:Creating metrics dataframe +2023-11-09 11:21:29,514:INFO:Uploading results into container +2023-11-09 11:21:29,514:INFO:Uploading model into container now +2023-11-09 11:21:29,515:INFO:_master_model_container: 9 +2023-11-09 11:21:29,515:INFO:_display_container: 2 +2023-11-09 11:21:29,515:INFO:PassiveAggressiveRegressor(random_state=123) +2023-11-09 11:21:29,515:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:29,665:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:29,665:INFO:Creating metrics dataframe +2023-11-09 11:21:29,695:INFO:Initializing Huber Regressor +2023-11-09 11:21:29,695:INFO:Total runtime is 0.07566508452097574 minutes +2023-11-09 11:21:29,701:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:29,702:INFO:Initializing create_model() +2023-11-09 11:21:29,702:INFO:create_model(self=, estimator=huber, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:29,702:INFO:Checking exceptions +2023-11-09 11:21:29,702:INFO:Importing libraries +2023-11-09 11:21:29,702:INFO:Copying training dataset +2023-11-09 11:21:29,709:INFO:Defining folds +2023-11-09 11:21:29,709:INFO:Declaring metric variables +2023-11-09 11:21:29,716:INFO:Importing untrained model +2023-11-09 11:21:29,721:INFO:Huber Regressor Imported successfully +2023-11-09 11:21:29,740:INFO:Starting cross validation +2023-11-09 11:21:29,741:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:29,859:INFO:Calculating mean and std +2023-11-09 11:21:29,860:INFO:Creating metrics dataframe +2023-11-09 11:21:29,864:INFO:Uploading results into container +2023-11-09 11:21:29,865:INFO:Uploading model into container now +2023-11-09 11:21:29,865:INFO:_master_model_container: 10 +2023-11-09 11:21:29,865:INFO:_display_container: 2 +2023-11-09 11:21:29,866:INFO:HuberRegressor() +2023-11-09 11:21:29,866:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:30,013:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:30,013:INFO:Creating metrics dataframe +2023-11-09 11:21:30,022:INFO:Initializing K Neighbors Regressor +2023-11-09 11:21:30,022:INFO:Total runtime is 0.08112245798110962 minutes +2023-11-09 11:21:30,026:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:30,026:INFO:Initializing create_model() +2023-11-09 11:21:30,026:INFO:create_model(self=, estimator=knn, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:30,027:INFO:Checking exceptions +2023-11-09 11:21:30,027:INFO:Importing libraries +2023-11-09 11:21:30,027:INFO:Copying training dataset +2023-11-09 11:21:30,030:INFO:Defining folds +2023-11-09 11:21:30,030:INFO:Declaring metric variables +2023-11-09 11:21:30,034:INFO:Importing untrained model +2023-11-09 11:21:30,038:INFO:K Neighbors Regressor Imported successfully +2023-11-09 11:21:30,044:INFO:Starting cross validation +2023-11-09 11:21:30,045:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:30,146:INFO:Calculating mean and std +2023-11-09 11:21:30,148:INFO:Creating metrics dataframe +2023-11-09 11:21:30,151:INFO:Uploading results into container +2023-11-09 11:21:30,152:INFO:Uploading model into container now +2023-11-09 11:21:30,153:INFO:_master_model_container: 11 +2023-11-09 11:21:30,153:INFO:_display_container: 2 +2023-11-09 11:21:30,153:INFO:KNeighborsRegressor(n_jobs=-1) +2023-11-09 11:21:30,153:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:30,291:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:30,291:INFO:Creating metrics dataframe +2023-11-09 11:21:30,302:INFO:Initializing Decision Tree Regressor +2023-11-09 11:21:30,302:INFO:Total runtime is 0.08578158617019653 minutes +2023-11-09 11:21:30,305:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:30,306:INFO:Initializing create_model() +2023-11-09 11:21:30,306:INFO:create_model(self=, estimator=dt, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:30,306:INFO:Checking exceptions +2023-11-09 11:21:30,306:INFO:Importing libraries +2023-11-09 11:21:30,306:INFO:Copying training dataset +2023-11-09 11:21:30,309:INFO:Defining folds +2023-11-09 11:21:30,310:INFO:Declaring metric variables +2023-11-09 11:21:30,314:INFO:Importing untrained model +2023-11-09 11:21:30,317:INFO:Decision Tree Regressor Imported successfully +2023-11-09 11:21:30,324:INFO:Starting cross validation +2023-11-09 11:21:30,325:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:30,401:INFO:Calculating mean and std +2023-11-09 11:21:30,402:INFO:Creating metrics dataframe +2023-11-09 11:21:30,405:INFO:Uploading results into container +2023-11-09 11:21:30,405:INFO:Uploading model into container now +2023-11-09 11:21:30,405:INFO:_master_model_container: 12 +2023-11-09 11:21:30,405:INFO:_display_container: 2 +2023-11-09 11:21:30,406:INFO:DecisionTreeRegressor(random_state=123) +2023-11-09 11:21:30,406:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:30,545:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:30,545:INFO:Creating metrics dataframe +2023-11-09 11:21:30,555:INFO:Initializing Random Forest Regressor +2023-11-09 11:21:30,555:INFO:Total runtime is 0.09000341494878134 minutes +2023-11-09 11:21:30,559:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:30,559:INFO:Initializing create_model() +2023-11-09 11:21:30,559:INFO:create_model(self=, estimator=rf, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:30,559:INFO:Checking exceptions +2023-11-09 11:21:30,560:INFO:Importing libraries +2023-11-09 11:21:30,560:INFO:Copying training dataset +2023-11-09 11:21:30,563:INFO:Defining folds +2023-11-09 11:21:30,563:INFO:Declaring metric variables +2023-11-09 11:21:30,566:INFO:Importing untrained model +2023-11-09 11:21:30,570:INFO:Random Forest Regressor Imported successfully +2023-11-09 11:21:30,577:INFO:Starting cross validation +2023-11-09 11:21:30,578:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:31,043:INFO:Calculating mean and std +2023-11-09 11:21:31,045:INFO:Creating metrics dataframe +2023-11-09 11:21:31,049:INFO:Uploading results into container +2023-11-09 11:21:31,050:INFO:Uploading model into container now +2023-11-09 11:21:31,050:INFO:_master_model_container: 13 +2023-11-09 11:21:31,051:INFO:_display_container: 2 +2023-11-09 11:21:31,052:INFO:RandomForestRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:21:31,052:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:31,256:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:31,257:INFO:Creating metrics dataframe +2023-11-09 11:21:31,273:INFO:Initializing Extra Trees Regressor +2023-11-09 11:21:31,273:INFO:Total runtime is 0.10196697314580282 minutes +2023-11-09 11:21:31,277:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:31,278:INFO:Initializing create_model() +2023-11-09 11:21:31,278:INFO:create_model(self=, estimator=et, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:31,278:INFO:Checking exceptions +2023-11-09 11:21:31,278:INFO:Importing libraries +2023-11-09 11:21:31,278:INFO:Copying training dataset +2023-11-09 11:21:31,282:INFO:Defining folds +2023-11-09 11:21:31,282:INFO:Declaring metric variables +2023-11-09 11:21:31,286:INFO:Importing untrained model +2023-11-09 11:21:31,289:INFO:Extra Trees Regressor Imported successfully +2023-11-09 11:21:31,296:INFO:Starting cross validation +2023-11-09 11:21:31,297:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:31,637:INFO:Calculating mean and std +2023-11-09 11:21:31,638:INFO:Creating metrics dataframe +2023-11-09 11:21:31,642:INFO:Uploading results into container +2023-11-09 11:21:31,643:INFO:Uploading model into container now +2023-11-09 11:21:31,644:INFO:_master_model_container: 14 +2023-11-09 11:21:31,644:INFO:_display_container: 2 +2023-11-09 11:21:31,644:INFO:ExtraTreesRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:21:31,644:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:31,780:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:31,780:INFO:Creating metrics dataframe +2023-11-09 11:21:31,790:INFO:Initializing AdaBoost Regressor +2023-11-09 11:21:31,790:INFO:Total runtime is 0.11058982610702514 minutes +2023-11-09 11:21:31,795:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:31,795:INFO:Initializing create_model() +2023-11-09 11:21:31,795:INFO:create_model(self=, estimator=ada, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:31,796:INFO:Checking exceptions +2023-11-09 11:21:31,796:INFO:Importing libraries +2023-11-09 11:21:31,796:INFO:Copying training dataset +2023-11-09 11:21:31,800:INFO:Defining folds +2023-11-09 11:21:31,800:INFO:Declaring metric variables +2023-11-09 11:21:31,804:INFO:Importing untrained model +2023-11-09 11:21:31,807:INFO:AdaBoost Regressor Imported successfully +2023-11-09 11:21:31,814:INFO:Starting cross validation +2023-11-09 11:21:31,816:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:32,017:INFO:Calculating mean and std +2023-11-09 11:21:32,018:INFO:Creating metrics dataframe +2023-11-09 11:21:32,021:INFO:Uploading results into container +2023-11-09 11:21:32,022:INFO:Uploading model into container now +2023-11-09 11:21:32,022:INFO:_master_model_container: 15 +2023-11-09 11:21:32,023:INFO:_display_container: 2 +2023-11-09 11:21:32,023:INFO:AdaBoostRegressor(random_state=123) +2023-11-09 11:21:32,023:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:32,156:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:32,156:INFO:Creating metrics dataframe +2023-11-09 11:21:32,167:INFO:Initializing Gradient Boosting Regressor +2023-11-09 11:21:32,168:INFO:Total runtime is 0.11687904198964437 minutes +2023-11-09 11:21:32,171:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:32,172:INFO:Initializing create_model() +2023-11-09 11:21:32,172:INFO:create_model(self=, estimator=gbr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:32,172:INFO:Checking exceptions +2023-11-09 11:21:32,172:INFO:Importing libraries +2023-11-09 11:21:32,172:INFO:Copying training dataset +2023-11-09 11:21:32,176:INFO:Defining folds +2023-11-09 11:21:32,176:INFO:Declaring metric variables +2023-11-09 11:21:32,180:INFO:Importing untrained model +2023-11-09 11:21:32,183:INFO:Gradient Boosting Regressor Imported successfully +2023-11-09 11:21:32,189:INFO:Starting cross validation +2023-11-09 11:21:32,190:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:32,373:INFO:Calculating mean and std +2023-11-09 11:21:32,374:INFO:Creating metrics dataframe +2023-11-09 11:21:32,378:INFO:Uploading results into container +2023-11-09 11:21:32,379:INFO:Uploading model into container now +2023-11-09 11:21:32,379:INFO:_master_model_container: 16 +2023-11-09 11:21:32,379:INFO:_display_container: 2 +2023-11-09 11:21:32,379:INFO:GradientBoostingRegressor(random_state=123) +2023-11-09 11:21:32,379:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:32,511:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:32,511:INFO:Creating metrics dataframe +2023-11-09 11:21:32,522:INFO:Initializing Light Gradient Boosting Machine +2023-11-09 11:21:32,522:INFO:Total runtime is 0.12278976440429687 minutes +2023-11-09 11:21:32,526:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:32,527:INFO:Initializing create_model() +2023-11-09 11:21:32,527:INFO:create_model(self=, estimator=lightgbm, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:32,527:INFO:Checking exceptions +2023-11-09 11:21:32,527:INFO:Importing libraries +2023-11-09 11:21:32,527:INFO:Copying training dataset +2023-11-09 11:21:32,531:INFO:Defining folds +2023-11-09 11:21:32,531:INFO:Declaring metric variables +2023-11-09 11:21:32,535:INFO:Importing untrained model +2023-11-09 11:21:32,538:INFO:Light Gradient Boosting Machine Imported successfully +2023-11-09 11:21:32,545:INFO:Starting cross validation +2023-11-09 11:21:32,546:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:32,899:INFO:Calculating mean and std +2023-11-09 11:21:32,900:INFO:Creating metrics dataframe +2023-11-09 11:21:32,905:INFO:Uploading results into container +2023-11-09 11:21:32,906:INFO:Uploading model into container now +2023-11-09 11:21:32,906:INFO:_master_model_container: 17 +2023-11-09 11:21:32,906:INFO:_display_container: 2 +2023-11-09 11:21:32,907:INFO:LGBMRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:21:32,907:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:33,038:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:33,038:INFO:Creating metrics dataframe +2023-11-09 11:21:33,049:INFO:Initializing Dummy Regressor +2023-11-09 11:21:33,050:INFO:Total runtime is 0.13158060709635416 minutes +2023-11-09 11:21:33,053:INFO:SubProcess create_model() called ================================== +2023-11-09 11:21:33,054:INFO:Initializing create_model() +2023-11-09 11:21:33,054:INFO:create_model(self=, estimator=dummy, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:33,054:INFO:Checking exceptions +2023-11-09 11:21:33,054:INFO:Importing libraries +2023-11-09 11:21:33,054:INFO:Copying training dataset +2023-11-09 11:21:33,058:INFO:Defining folds +2023-11-09 11:21:33,058:INFO:Declaring metric variables +2023-11-09 11:21:33,061:INFO:Importing untrained model +2023-11-09 11:21:33,064:INFO:Dummy Regressor Imported successfully +2023-11-09 11:21:33,071:INFO:Starting cross validation +2023-11-09 11:21:33,072:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:21:33,142:INFO:Calculating mean and std +2023-11-09 11:21:33,142:INFO:Creating metrics dataframe +2023-11-09 11:21:33,145:INFO:Uploading results into container +2023-11-09 11:21:33,146:INFO:Uploading model into container now +2023-11-09 11:21:33,146:INFO:_master_model_container: 18 +2023-11-09 11:21:33,146:INFO:_display_container: 2 +2023-11-09 11:21:33,146:INFO:DummyRegressor() +2023-11-09 11:21:33,146:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:33,312:INFO:SubProcess create_model() end ================================== +2023-11-09 11:21:33,313:INFO:Creating metrics dataframe +2023-11-09 11:21:33,341:INFO:Initializing create_model() +2023-11-09 11:21:33,341:INFO:create_model(self=, estimator=HuberRegressor(), fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=False, predict=False, fit_kwargs={}, groups=None, refit=True, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=None, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:21:33,341:INFO:Checking exceptions +2023-11-09 11:21:33,343:INFO:Importing libraries +2023-11-09 11:21:33,344:INFO:Copying training dataset +2023-11-09 11:21:33,347:INFO:Defining folds +2023-11-09 11:21:33,347:INFO:Declaring metric variables +2023-11-09 11:21:33,347:INFO:Importing untrained model +2023-11-09 11:21:33,347:INFO:Declaring custom model +2023-11-09 11:21:33,348:INFO:Huber Regressor Imported successfully +2023-11-09 11:21:33,349:INFO:Cross validation set to False +2023-11-09 11:21:33,349:INFO:Fitting Model +2023-11-09 11:21:33,371:INFO:HuberRegressor() +2023-11-09 11:21:33,371:INFO:create_model() successfully completed...................................... +2023-11-09 11:21:33,531:INFO:_master_model_container: 18 +2023-11-09 11:21:33,532:INFO:_display_container: 2 +2023-11-09 11:21:33,532:INFO:HuberRegressor() +2023-11-09 11:21:33,532:INFO:compare_models() successfully completed...................................... +2023-11-09 11:21:33,686:INFO:Initializing predict_model() +2023-11-09 11:21:33,686:INFO:predict_model(self=, estimator=HuberRegressor(), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=.encode_labels at 0x7fbb2cbd5310>) +2023-11-09 11:21:33,687:INFO:Checking exceptions +2023-11-09 11:21:33,687:INFO:Preloading libraries +2023-11-09 11:21:33,688:INFO:Set up data. +2023-11-09 11:21:33,691:INFO:Set up index. +2023-11-09 11:21:34,187:WARNING:/tmp/ipykernel_54540/4098162356.py:1: SettingWithCopyWarning: + + +A value is trying to be set on a copy of a slice from a DataFrame + +See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy + + +2023-11-09 11:21:40,590:WARNING:/tmp/ipykernel_54540/716735288.py:1: SettingWithCopyWarning: + + +A value is trying to be set on a copy of a slice from a DataFrame + +See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy + + +2023-11-09 11:22:00,516:INFO:PyCaret RegressionExperiment +2023-11-09 11:22:00,518:INFO:Logging name: reg-default-name +2023-11-09 11:22:00,519:INFO:ML Usecase: MLUsecase.REGRESSION +2023-11-09 11:22:00,519:INFO:version 3.1.0 +2023-11-09 11:22:00,519:INFO:Initializing setup() +2023-11-09 11:22:00,519:INFO:self.USI: d493 +2023-11-09 11:22:00,519:INFO:self._variable_keys: {'seed', 'idx', 'transform_target_param', 'gpu_param', 'target_param', 'log_plots_param', 'pipeline', 'logging_param', 'fold_groups_param', '_ml_usecase', 'html_param', 'gpu_n_jobs_param', 'y', 'y_test', 'y_train', 'memory', 'exp_id', 'X_test', 'exp_name_log', 'USI', 'data', 'X_train', 'fold_shuffle_param', 'X', 'fold_generator', 'n_jobs_param', '_available_plots'} +2023-11-09 11:22:00,519:INFO:Checking environment +2023-11-09 11:22:00,519:INFO:python_version: 3.8.18 +2023-11-09 11:22:00,520:INFO:python_build: ('default', 'Sep 11 2023 13:40:15') +2023-11-09 11:22:00,520:INFO:machine: x86_64 +2023-11-09 11:22:00,520:INFO:platform: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:22:00,520:INFO:Memory: svmem(total=8315187200, available=4558508032, percent=45.2, used=3422035968, free=207908864, active=1474625536, inactive=5763665920, buffers=337895424, cached=4347346944, shared=4485120, slab=651317248) +2023-11-09 11:22:00,520:INFO:Physical Core: 1 +2023-11-09 11:22:00,520:INFO:Logical Core: 2 +2023-11-09 11:22:00,520:INFO:Checking libraries +2023-11-09 11:22:00,520:INFO:System: +2023-11-09 11:22:00,520:INFO: python: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] +2023-11-09 11:22:00,520:INFO:executable: /workspaces/D2I-Jupyter-Notebook-Tools/.conda/bin/python +2023-11-09 11:22:00,520:INFO: machine: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:22:00,521:INFO:PyCaret required dependencies: +2023-11-09 11:22:00,521:INFO: pip: 23.3 +2023-11-09 11:22:00,521:INFO: setuptools: 68.0.0 +2023-11-09 11:22:00,521:INFO: pycaret: 3.1.0 +2023-11-09 11:22:00,521:INFO: IPython: 8.12.0 +2023-11-09 11:22:00,521:INFO: ipywidgets: 8.1.1 +2023-11-09 11:22:00,521:INFO: tqdm: 4.66.1 +2023-11-09 11:22:00,521:INFO: numpy: 1.23.5 +2023-11-09 11:22:00,521:INFO: pandas: 1.5.3 +2023-11-09 11:22:00,521:INFO: jinja2: 3.1.2 +2023-11-09 11:22:00,521:INFO: scipy: 1.10.1 +2023-11-09 11:22:00,521:INFO: joblib: 1.3.2 +2023-11-09 11:22:00,521:INFO: sklearn: 1.2.2 +2023-11-09 11:22:00,521:INFO: pyod: 1.1.1 +2023-11-09 11:22:00,521:INFO: imblearn: 0.11.0 +2023-11-09 11:22:00,521:INFO: category_encoders: 2.6.3 +2023-11-09 11:22:00,521:INFO: lightgbm: 4.1.0 +2023-11-09 11:22:00,521:INFO: numba: 0.58.1 +2023-11-09 11:22:00,522:INFO: requests: 2.31.0 +2023-11-09 11:22:00,522:INFO: matplotlib: 3.7.3 +2023-11-09 11:22:00,522:INFO: scikitplot: 0.3.7 +2023-11-09 11:22:00,522:INFO: yellowbrick: 1.5 +2023-11-09 11:22:00,522:INFO: plotly: 5.18.0 +2023-11-09 11:22:00,522:INFO: plotly-resampler: Not installed +2023-11-09 11:22:00,522:INFO: kaleido: 0.2.1 +2023-11-09 11:22:00,522:INFO: schemdraw: 0.15 +2023-11-09 11:22:00,522:INFO: statsmodels: 0.14.0 +2023-11-09 11:22:00,522:INFO: sktime: 0.21.1 +2023-11-09 11:22:00,522:INFO: tbats: 1.1.3 +2023-11-09 11:22:00,522:INFO: pmdarima: 2.0.4 +2023-11-09 11:22:00,522:INFO: psutil: 5.9.0 +2023-11-09 11:22:00,522:INFO: markupsafe: 2.1.3 +2023-11-09 11:22:00,522:INFO: pickle5: Not installed +2023-11-09 11:22:00,522:INFO: cloudpickle: 3.0.0 +2023-11-09 11:22:00,522:INFO: deprecation: 2.1.0 +2023-11-09 11:22:00,523:INFO: xxhash: 3.4.1 +2023-11-09 11:22:00,523:INFO: wurlitzer: 3.0.3 +2023-11-09 11:22:00,523:INFO:PyCaret optional dependencies: +2023-11-09 11:22:00,523:INFO: shap: Not installed +2023-11-09 11:22:00,523:INFO: interpret: Not installed +2023-11-09 11:22:00,523:INFO: umap: Not installed +2023-11-09 11:22:00,523:INFO: ydata_profiling: Not installed +2023-11-09 11:22:00,523:INFO: explainerdashboard: Not installed +2023-11-09 11:22:00,523:INFO: autoviz: Not installed +2023-11-09 11:22:00,523:INFO: fairlearn: Not installed +2023-11-09 11:22:00,523:INFO: deepchecks: Not installed +2023-11-09 11:22:00,523:INFO: xgboost: Not installed +2023-11-09 11:22:00,523:INFO: catboost: Not installed +2023-11-09 11:22:00,523:INFO: kmodes: Not installed +2023-11-09 11:22:00,523:INFO: mlxtend: Not installed +2023-11-09 11:22:00,523:INFO: statsforecast: Not installed +2023-11-09 11:22:00,523:INFO: tune_sklearn: Not installed +2023-11-09 11:22:00,524:INFO: ray: Not installed +2023-11-09 11:22:00,524:INFO: hyperopt: Not installed +2023-11-09 11:22:00,524:INFO: optuna: Not installed +2023-11-09 11:22:00,524:INFO: skopt: Not installed +2023-11-09 11:22:00,524:INFO: mlflow: Not installed +2023-11-09 11:22:00,524:INFO: gradio: Not installed +2023-11-09 11:22:00,524:INFO: fastapi: Not installed +2023-11-09 11:22:00,524:INFO: uvicorn: Not installed +2023-11-09 11:22:00,524:INFO: m2cgen: Not installed +2023-11-09 11:22:00,524:INFO: evidently: Not installed +2023-11-09 11:22:00,524:INFO: fugue: Not installed +2023-11-09 11:22:00,524:INFO: streamlit: Not installed +2023-11-09 11:22:00,524:INFO: prophet: Not installed +2023-11-09 11:22:00,524:INFO:None +2023-11-09 11:22:00,524:INFO:Set up data. +2023-11-09 11:22:00,528:INFO:Set up folding strategy. +2023-11-09 11:22:00,528:INFO:Set up train/test split. +2023-11-09 11:22:00,528:INFO:Set up data. +2023-11-09 11:22:00,531:INFO:Set up index. +2023-11-09 11:22:00,532:INFO:Assigning column types. +2023-11-09 11:22:00,534:INFO:Engine successfully changes for model 'lr' to 'sklearn'. +2023-11-09 11:22:00,534:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,538:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,542:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,597:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,635:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,636:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:00,636:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:00,637:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,641:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,645:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,694:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,745:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,745:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:00,746:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:00,746:INFO:Engine successfully changes for model 'lasso' to 'sklearn'. +2023-11-09 11:22:00,750:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,754:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,801:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,839:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,839:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:00,840:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:00,844:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,848:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,895:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,933:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,933:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:00,933:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:00,934:INFO:Engine successfully changes for model 'ridge' to 'sklearn'. +2023-11-09 11:22:00,941:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:22:00,988:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:22:01,025:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:22:01,026:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,026:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,034:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:22:01,081:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:22:01,125:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:22:01,127:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,127:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,127:INFO:Engine successfully changes for model 'en' to 'sklearn'. +2023-11-09 11:22:01,223:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:22:01,260:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:22:01,261:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,261:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,317:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:22:01,354:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:22:01,355:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,355:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,356:INFO:Engine successfully changes for model 'knn' to 'sklearn'. +2023-11-09 11:22:01,436:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:22:01,473:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,473:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,538:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:22:01,576:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,576:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,577:INFO:Engine successfully changes for model 'svm' to 'sklearn'. +2023-11-09 11:22:01,672:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,672:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,816:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,817:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:01,818:INFO:Preparing preprocessing pipeline... +2023-11-09 11:22:01,818:INFO:Set up target transformation. +2023-11-09 11:22:01,818:INFO:Set up simple imputation. +2023-11-09 11:22:01,818:INFO:Set up column name cleaning. +2023-11-09 11:22:01,858:INFO:Finished creating preprocessing pipeline. +2023-11-09 11:22:01,867:INFO:Pipeline: Pipeline(memory=FastMemory(location=/tmp/joblib), + steps=[('target_transformation', + TransformerWrapperWithInverse(transformer=TargetTransformer(estimator=PowerTransformer(standardize=False)))), + ('numerical_imputer', + TransformerWrapper(include=['Year', 'Series'], + transformer=SimpleImputer())), + ('categorical_imputer', + TransformerWrapper(include=[], + transformer=SimpleImputer(strategy='most_frequent'))), + ('clean_column_names', + TransformerWrapper(transformer=CleanColumnNames()))]) +2023-11-09 11:22:01,867:INFO:Creating final display dataframe. +2023-11-09 11:22:01,963:INFO:Setup _display_container: Description Value +0 Session id 123 +1 Target Average price All property types +2 Target type Regression +3 Original data shape (523, 4) +4 Transformed data shape (523, 4) +5 Transformed train set shape (372, 4) +6 Transformed test set shape (151, 4) +7 Numeric features 2 +8 Preprocess True +9 Imputation type simple +10 Numeric imputation mean +11 Categorical imputation mode +12 Transform target True +13 Transform target method yeo-johnson +14 Fold Generator TimeSeriesSplit +15 Fold Number 3 +16 CPU Jobs -1 +17 Use GPU False +18 Log Experiment False +19 Experiment Name reg-default-name +20 USI d493 +2023-11-09 11:22:02,119:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:02,119:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:02,219:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:02,219:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:22:02,220:INFO:setup() successfully completed in 1.7s............... +2023-11-09 11:22:02,289:INFO:Initializing compare_models() +2023-11-09 11:22:02,289:INFO:compare_models(self=, include=None, fold=None, round=4, cross_validation=True, sort=MAE, n_select=1, budget_time=None, turbo=True, errors=ignore, fit_kwargs=None, groups=None, experiment_custom_tags=None, probability_threshold=None, verbose=True, parallel=None, caller_params={'self': , 'include': None, 'exclude': None, 'fold': None, 'round': 4, 'cross_validation': True, 'sort': 'MAE', 'n_select': 1, 'budget_time': None, 'turbo': True, 'errors': 'ignore', 'fit_kwargs': None, 'groups': None, 'experiment_custom_tags': None, 'engine': None, 'verbose': True, 'parallel': None, '__class__': }, exclude=None) +2023-11-09 11:22:02,289:INFO:Checking exceptions +2023-11-09 11:22:02,293:INFO:Preparing display monitor +2023-11-09 11:22:02,314:INFO:Initializing Linear Regression +2023-11-09 11:22:02,314:INFO:Total runtime is 4.541873931884766e-06 minutes +2023-11-09 11:22:02,317:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:02,318:INFO:Initializing create_model() +2023-11-09 11:22:02,318:INFO:create_model(self=, estimator=lr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:02,318:INFO:Checking exceptions +2023-11-09 11:22:02,318:INFO:Importing libraries +2023-11-09 11:22:02,319:INFO:Copying training dataset +2023-11-09 11:22:02,321:INFO:Defining folds +2023-11-09 11:22:02,321:INFO:Declaring metric variables +2023-11-09 11:22:02,324:INFO:Importing untrained model +2023-11-09 11:22:02,327:INFO:Linear Regression Imported successfully +2023-11-09 11:22:02,334:INFO:Starting cross validation +2023-11-09 11:22:02,335:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:02,415:INFO:Calculating mean and std +2023-11-09 11:22:02,416:INFO:Creating metrics dataframe +2023-11-09 11:22:02,420:INFO:Uploading results into container +2023-11-09 11:22:02,421:INFO:Uploading model into container now +2023-11-09 11:22:02,421:INFO:_master_model_container: 1 +2023-11-09 11:22:02,421:INFO:_display_container: 2 +2023-11-09 11:22:02,422:INFO:LinearRegression(n_jobs=-1) +2023-11-09 11:22:02,422:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:02,589:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:02,589:INFO:Creating metrics dataframe +2023-11-09 11:22:02,597:INFO:Initializing Lasso Regression +2023-11-09 11:22:02,597:INFO:Total runtime is 0.004718661308288574 minutes +2023-11-09 11:22:02,601:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:02,601:INFO:Initializing create_model() +2023-11-09 11:22:02,601:INFO:create_model(self=, estimator=lasso, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:02,602:INFO:Checking exceptions +2023-11-09 11:22:02,602:INFO:Importing libraries +2023-11-09 11:22:02,602:INFO:Copying training dataset +2023-11-09 11:22:02,605:INFO:Defining folds +2023-11-09 11:22:02,605:INFO:Declaring metric variables +2023-11-09 11:22:02,608:INFO:Importing untrained model +2023-11-09 11:22:02,611:INFO:Lasso Regression Imported successfully +2023-11-09 11:22:02,617:INFO:Starting cross validation +2023-11-09 11:22:02,618:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:02,695:INFO:Calculating mean and std +2023-11-09 11:22:02,696:INFO:Creating metrics dataframe +2023-11-09 11:22:02,698:INFO:Uploading results into container +2023-11-09 11:22:02,699:INFO:Uploading model into container now +2023-11-09 11:22:02,699:INFO:_master_model_container: 2 +2023-11-09 11:22:02,699:INFO:_display_container: 2 +2023-11-09 11:22:02,700:INFO:Lasso(random_state=123) +2023-11-09 11:22:02,700:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:02,828:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:02,828:INFO:Creating metrics dataframe +2023-11-09 11:22:02,836:INFO:Initializing Ridge Regression +2023-11-09 11:22:02,837:INFO:Total runtime is 0.008710046609242756 minutes +2023-11-09 11:22:02,840:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:02,841:INFO:Initializing create_model() +2023-11-09 11:22:02,841:INFO:create_model(self=, estimator=ridge, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:02,841:INFO:Checking exceptions +2023-11-09 11:22:02,841:INFO:Importing libraries +2023-11-09 11:22:02,841:INFO:Copying training dataset +2023-11-09 11:22:02,844:INFO:Defining folds +2023-11-09 11:22:02,844:INFO:Declaring metric variables +2023-11-09 11:22:02,847:INFO:Importing untrained model +2023-11-09 11:22:02,850:INFO:Ridge Regression Imported successfully +2023-11-09 11:22:02,856:INFO:Starting cross validation +2023-11-09 11:22:02,857:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:02,938:INFO:Calculating mean and std +2023-11-09 11:22:02,939:INFO:Creating metrics dataframe +2023-11-09 11:22:02,942:INFO:Uploading results into container +2023-11-09 11:22:02,942:INFO:Uploading model into container now +2023-11-09 11:22:02,942:INFO:_master_model_container: 3 +2023-11-09 11:22:02,942:INFO:_display_container: 2 +2023-11-09 11:22:02,943:INFO:Ridge(random_state=123) +2023-11-09 11:22:02,943:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:03,073:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:03,073:INFO:Creating metrics dataframe +2023-11-09 11:22:03,081:INFO:Initializing Elastic Net +2023-11-09 11:22:03,081:INFO:Total runtime is 0.012786833445231119 minutes +2023-11-09 11:22:03,085:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:03,085:INFO:Initializing create_model() +2023-11-09 11:22:03,085:INFO:create_model(self=, estimator=en, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:03,085:INFO:Checking exceptions +2023-11-09 11:22:03,085:INFO:Importing libraries +2023-11-09 11:22:03,085:INFO:Copying training dataset +2023-11-09 11:22:03,088:INFO:Defining folds +2023-11-09 11:22:03,088:INFO:Declaring metric variables +2023-11-09 11:22:03,091:INFO:Importing untrained model +2023-11-09 11:22:03,094:INFO:Elastic Net Imported successfully +2023-11-09 11:22:03,100:INFO:Starting cross validation +2023-11-09 11:22:03,101:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:03,178:INFO:Calculating mean and std +2023-11-09 11:22:03,178:INFO:Creating metrics dataframe +2023-11-09 11:22:03,181:INFO:Uploading results into container +2023-11-09 11:22:03,181:INFO:Uploading model into container now +2023-11-09 11:22:03,182:INFO:_master_model_container: 4 +2023-11-09 11:22:03,182:INFO:_display_container: 2 +2023-11-09 11:22:03,182:INFO:ElasticNet(random_state=123) +2023-11-09 11:22:03,182:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:03,306:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:03,306:INFO:Creating metrics dataframe +2023-11-09 11:22:03,316:INFO:Initializing Least Angle Regression +2023-11-09 11:22:03,316:INFO:Total runtime is 0.016691342989603678 minutes +2023-11-09 11:22:03,319:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:03,319:INFO:Initializing create_model() +2023-11-09 11:22:03,319:INFO:create_model(self=, estimator=lar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:03,320:INFO:Checking exceptions +2023-11-09 11:22:03,320:INFO:Importing libraries +2023-11-09 11:22:03,320:INFO:Copying training dataset +2023-11-09 11:22:03,324:INFO:Defining folds +2023-11-09 11:22:03,324:INFO:Declaring metric variables +2023-11-09 11:22:03,328:INFO:Importing untrained model +2023-11-09 11:22:03,331:INFO:Least Angle Regression Imported successfully +2023-11-09 11:22:03,337:INFO:Starting cross validation +2023-11-09 11:22:03,338:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:03,415:INFO:Calculating mean and std +2023-11-09 11:22:03,416:INFO:Creating metrics dataframe +2023-11-09 11:22:03,418:INFO:Uploading results into container +2023-11-09 11:22:03,419:INFO:Uploading model into container now +2023-11-09 11:22:03,419:INFO:_master_model_container: 5 +2023-11-09 11:22:03,419:INFO:_display_container: 2 +2023-11-09 11:22:03,419:INFO:Lars(random_state=123) +2023-11-09 11:22:03,419:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:03,538:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:03,538:INFO:Creating metrics dataframe +2023-11-09 11:22:03,547:INFO:Initializing Lasso Least Angle Regression +2023-11-09 11:22:03,547:INFO:Total runtime is 0.020549750328063963 minutes +2023-11-09 11:22:03,551:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:03,551:INFO:Initializing create_model() +2023-11-09 11:22:03,551:INFO:create_model(self=, estimator=llar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:03,551:INFO:Checking exceptions +2023-11-09 11:22:03,551:INFO:Importing libraries +2023-11-09 11:22:03,551:INFO:Copying training dataset +2023-11-09 11:22:03,555:INFO:Defining folds +2023-11-09 11:22:03,556:INFO:Declaring metric variables +2023-11-09 11:22:03,559:INFO:Importing untrained model +2023-11-09 11:22:03,562:INFO:Lasso Least Angle Regression Imported successfully +2023-11-09 11:22:03,568:INFO:Starting cross validation +2023-11-09 11:22:03,569:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:03,645:INFO:Calculating mean and std +2023-11-09 11:22:03,645:INFO:Creating metrics dataframe +2023-11-09 11:22:03,648:INFO:Uploading results into container +2023-11-09 11:22:03,648:INFO:Uploading model into container now +2023-11-09 11:22:03,649:INFO:_master_model_container: 6 +2023-11-09 11:22:03,649:INFO:_display_container: 2 +2023-11-09 11:22:03,649:INFO:LassoLars(random_state=123) +2023-11-09 11:22:03,649:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:03,780:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:03,780:INFO:Creating metrics dataframe +2023-11-09 11:22:03,791:INFO:Initializing Orthogonal Matching Pursuit +2023-11-09 11:22:03,792:INFO:Total runtime is 0.024624423185984293 minutes +2023-11-09 11:22:03,795:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:03,796:INFO:Initializing create_model() +2023-11-09 11:22:03,796:INFO:create_model(self=, estimator=omp, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:03,796:INFO:Checking exceptions +2023-11-09 11:22:03,796:INFO:Importing libraries +2023-11-09 11:22:03,796:INFO:Copying training dataset +2023-11-09 11:22:03,800:INFO:Defining folds +2023-11-09 11:22:03,800:INFO:Declaring metric variables +2023-11-09 11:22:03,804:INFO:Importing untrained model +2023-11-09 11:22:03,807:INFO:Orthogonal Matching Pursuit Imported successfully +2023-11-09 11:22:03,813:INFO:Starting cross validation +2023-11-09 11:22:03,815:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:03,886:INFO:Calculating mean and std +2023-11-09 11:22:03,886:INFO:Creating metrics dataframe +2023-11-09 11:22:03,889:INFO:Uploading results into container +2023-11-09 11:22:03,889:INFO:Uploading model into container now +2023-11-09 11:22:03,890:INFO:_master_model_container: 7 +2023-11-09 11:22:03,890:INFO:_display_container: 2 +2023-11-09 11:22:03,890:INFO:OrthogonalMatchingPursuit() +2023-11-09 11:22:03,891:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:04,019:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:04,019:INFO:Creating metrics dataframe +2023-11-09 11:22:04,028:INFO:Initializing Bayesian Ridge +2023-11-09 11:22:04,028:INFO:Total runtime is 0.02857042948404948 minutes +2023-11-09 11:22:04,032:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:04,032:INFO:Initializing create_model() +2023-11-09 11:22:04,032:INFO:create_model(self=, estimator=br, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:04,032:INFO:Checking exceptions +2023-11-09 11:22:04,032:INFO:Importing libraries +2023-11-09 11:22:04,032:INFO:Copying training dataset +2023-11-09 11:22:04,036:INFO:Defining folds +2023-11-09 11:22:04,036:INFO:Declaring metric variables +2023-11-09 11:22:04,040:INFO:Importing untrained model +2023-11-09 11:22:04,043:INFO:Bayesian Ridge Imported successfully +2023-11-09 11:22:04,049:INFO:Starting cross validation +2023-11-09 11:22:04,050:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:04,127:INFO:Calculating mean and std +2023-11-09 11:22:04,128:INFO:Creating metrics dataframe +2023-11-09 11:22:04,130:INFO:Uploading results into container +2023-11-09 11:22:04,131:INFO:Uploading model into container now +2023-11-09 11:22:04,131:INFO:_master_model_container: 8 +2023-11-09 11:22:04,131:INFO:_display_container: 2 +2023-11-09 11:22:04,132:INFO:BayesianRidge() +2023-11-09 11:22:04,132:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:04,256:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:04,256:INFO:Creating metrics dataframe +2023-11-09 11:22:04,266:INFO:Initializing Passive Aggressive Regressor +2023-11-09 11:22:04,266:INFO:Total runtime is 0.03253678480784098 minutes +2023-11-09 11:22:04,270:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:04,270:INFO:Initializing create_model() +2023-11-09 11:22:04,270:INFO:create_model(self=, estimator=par, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:04,270:INFO:Checking exceptions +2023-11-09 11:22:04,270:INFO:Importing libraries +2023-11-09 11:22:04,270:INFO:Copying training dataset +2023-11-09 11:22:04,274:INFO:Defining folds +2023-11-09 11:22:04,275:INFO:Declaring metric variables +2023-11-09 11:22:04,278:INFO:Importing untrained model +2023-11-09 11:22:04,282:INFO:Passive Aggressive Regressor Imported successfully +2023-11-09 11:22:04,287:INFO:Starting cross validation +2023-11-09 11:22:04,289:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:04,371:INFO:Calculating mean and std +2023-11-09 11:22:04,372:INFO:Creating metrics dataframe +2023-11-09 11:22:04,375:INFO:Uploading results into container +2023-11-09 11:22:04,376:INFO:Uploading model into container now +2023-11-09 11:22:04,377:INFO:_master_model_container: 9 +2023-11-09 11:22:04,377:INFO:_display_container: 2 +2023-11-09 11:22:04,379:INFO:PassiveAggressiveRegressor(random_state=123) +2023-11-09 11:22:04,379:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:04,514:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:04,514:INFO:Creating metrics dataframe +2023-11-09 11:22:04,524:INFO:Initializing Huber Regressor +2023-11-09 11:22:04,524:INFO:Total runtime is 0.036831418673197426 minutes +2023-11-09 11:22:04,527:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:04,528:INFO:Initializing create_model() +2023-11-09 11:22:04,528:INFO:create_model(self=, estimator=huber, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:04,529:INFO:Checking exceptions +2023-11-09 11:22:04,529:INFO:Importing libraries +2023-11-09 11:22:04,529:INFO:Copying training dataset +2023-11-09 11:22:04,533:INFO:Defining folds +2023-11-09 11:22:04,533:INFO:Declaring metric variables +2023-11-09 11:22:04,536:INFO:Importing untrained model +2023-11-09 11:22:04,539:INFO:Huber Regressor Imported successfully +2023-11-09 11:22:04,545:INFO:Starting cross validation +2023-11-09 11:22:04,546:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:04,708:INFO:Calculating mean and std +2023-11-09 11:22:04,710:INFO:Creating metrics dataframe +2023-11-09 11:22:04,714:INFO:Uploading results into container +2023-11-09 11:22:04,716:INFO:Uploading model into container now +2023-11-09 11:22:04,719:INFO:_master_model_container: 10 +2023-11-09 11:22:04,719:INFO:_display_container: 2 +2023-11-09 11:22:04,719:INFO:HuberRegressor() +2023-11-09 11:22:04,719:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:04,865:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:04,865:INFO:Creating metrics dataframe +2023-11-09 11:22:04,875:INFO:Initializing K Neighbors Regressor +2023-11-09 11:22:04,875:INFO:Total runtime is 0.04268600543340047 minutes +2023-11-09 11:22:04,879:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:04,880:INFO:Initializing create_model() +2023-11-09 11:22:04,880:INFO:create_model(self=, estimator=knn, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:04,880:INFO:Checking exceptions +2023-11-09 11:22:04,880:INFO:Importing libraries +2023-11-09 11:22:04,880:INFO:Copying training dataset +2023-11-09 11:22:04,884:INFO:Defining folds +2023-11-09 11:22:04,884:INFO:Declaring metric variables +2023-11-09 11:22:04,888:INFO:Importing untrained model +2023-11-09 11:22:04,892:INFO:K Neighbors Regressor Imported successfully +2023-11-09 11:22:04,898:INFO:Starting cross validation +2023-11-09 11:22:04,899:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:04,994:INFO:Calculating mean and std +2023-11-09 11:22:04,995:INFO:Creating metrics dataframe +2023-11-09 11:22:04,999:INFO:Uploading results into container +2023-11-09 11:22:04,999:INFO:Uploading model into container now +2023-11-09 11:22:05,000:INFO:_master_model_container: 11 +2023-11-09 11:22:05,000:INFO:_display_container: 2 +2023-11-09 11:22:05,000:INFO:KNeighborsRegressor(n_jobs=-1) +2023-11-09 11:22:05,000:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:05,122:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:05,122:INFO:Creating metrics dataframe +2023-11-09 11:22:05,132:INFO:Initializing Decision Tree Regressor +2023-11-09 11:22:05,132:INFO:Total runtime is 0.04696792761484782 minutes +2023-11-09 11:22:05,136:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:05,136:INFO:Initializing create_model() +2023-11-09 11:22:05,136:INFO:create_model(self=, estimator=dt, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:05,136:INFO:Checking exceptions +2023-11-09 11:22:05,136:INFO:Importing libraries +2023-11-09 11:22:05,136:INFO:Copying training dataset +2023-11-09 11:22:05,140:INFO:Defining folds +2023-11-09 11:22:05,140:INFO:Declaring metric variables +2023-11-09 11:22:05,143:INFO:Importing untrained model +2023-11-09 11:22:05,149:INFO:Decision Tree Regressor Imported successfully +2023-11-09 11:22:05,158:INFO:Starting cross validation +2023-11-09 11:22:05,159:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:05,300:INFO:Calculating mean and std +2023-11-09 11:22:05,301:INFO:Creating metrics dataframe +2023-11-09 11:22:05,305:INFO:Uploading results into container +2023-11-09 11:22:05,305:INFO:Uploading model into container now +2023-11-09 11:22:05,306:INFO:_master_model_container: 12 +2023-11-09 11:22:05,306:INFO:_display_container: 2 +2023-11-09 11:22:05,306:INFO:DecisionTreeRegressor(random_state=123) +2023-11-09 11:22:05,307:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:05,438:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:05,438:INFO:Creating metrics dataframe +2023-11-09 11:22:05,452:INFO:Initializing Random Forest Regressor +2023-11-09 11:22:05,452:INFO:Total runtime is 0.052305356661478675 minutes +2023-11-09 11:22:05,456:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:05,456:INFO:Initializing create_model() +2023-11-09 11:22:05,457:INFO:create_model(self=, estimator=rf, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:05,457:INFO:Checking exceptions +2023-11-09 11:22:05,457:INFO:Importing libraries +2023-11-09 11:22:05,457:INFO:Copying training dataset +2023-11-09 11:22:05,460:INFO:Defining folds +2023-11-09 11:22:05,461:INFO:Declaring metric variables +2023-11-09 11:22:05,464:INFO:Importing untrained model +2023-11-09 11:22:05,467:INFO:Random Forest Regressor Imported successfully +2023-11-09 11:22:05,474:INFO:Starting cross validation +2023-11-09 11:22:05,475:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:05,883:INFO:Calculating mean and std +2023-11-09 11:22:05,884:INFO:Creating metrics dataframe +2023-11-09 11:22:05,888:INFO:Uploading results into container +2023-11-09 11:22:05,889:INFO:Uploading model into container now +2023-11-09 11:22:05,890:INFO:_master_model_container: 13 +2023-11-09 11:22:05,890:INFO:_display_container: 2 +2023-11-09 11:22:05,890:INFO:RandomForestRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:22:05,890:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:06,025:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:06,025:INFO:Creating metrics dataframe +2023-11-09 11:22:06,035:INFO:Initializing Extra Trees Regressor +2023-11-09 11:22:06,036:INFO:Total runtime is 0.062024883429209386 minutes +2023-11-09 11:22:06,039:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:06,040:INFO:Initializing create_model() +2023-11-09 11:22:06,040:INFO:create_model(self=, estimator=et, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:06,040:INFO:Checking exceptions +2023-11-09 11:22:06,040:INFO:Importing libraries +2023-11-09 11:22:06,040:INFO:Copying training dataset +2023-11-09 11:22:06,043:INFO:Defining folds +2023-11-09 11:22:06,043:INFO:Declaring metric variables +2023-11-09 11:22:06,048:INFO:Importing untrained model +2023-11-09 11:22:06,052:INFO:Extra Trees Regressor Imported successfully +2023-11-09 11:22:06,058:INFO:Starting cross validation +2023-11-09 11:22:06,060:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:06,387:INFO:Calculating mean and std +2023-11-09 11:22:06,388:INFO:Creating metrics dataframe +2023-11-09 11:22:06,392:INFO:Uploading results into container +2023-11-09 11:22:06,393:INFO:Uploading model into container now +2023-11-09 11:22:06,393:INFO:_master_model_container: 14 +2023-11-09 11:22:06,393:INFO:_display_container: 2 +2023-11-09 11:22:06,393:INFO:ExtraTreesRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:22:06,393:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:06,542:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:06,542:INFO:Creating metrics dataframe +2023-11-09 11:22:06,552:INFO:Initializing AdaBoost Regressor +2023-11-09 11:22:06,553:INFO:Total runtime is 0.07064069112141927 minutes +2023-11-09 11:22:06,556:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:06,557:INFO:Initializing create_model() +2023-11-09 11:22:06,557:INFO:create_model(self=, estimator=ada, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:06,557:INFO:Checking exceptions +2023-11-09 11:22:06,557:INFO:Importing libraries +2023-11-09 11:22:06,557:INFO:Copying training dataset +2023-11-09 11:22:06,561:INFO:Defining folds +2023-11-09 11:22:06,562:INFO:Declaring metric variables +2023-11-09 11:22:06,565:INFO:Importing untrained model +2023-11-09 11:22:06,568:INFO:AdaBoost Regressor Imported successfully +2023-11-09 11:22:06,574:INFO:Starting cross validation +2023-11-09 11:22:06,575:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:06,802:INFO:Calculating mean and std +2023-11-09 11:22:06,803:INFO:Creating metrics dataframe +2023-11-09 11:22:06,809:INFO:Uploading results into container +2023-11-09 11:22:06,810:INFO:Uploading model into container now +2023-11-09 11:22:06,811:INFO:_master_model_container: 15 +2023-11-09 11:22:06,811:INFO:_display_container: 2 +2023-11-09 11:22:06,812:INFO:AdaBoostRegressor(random_state=123) +2023-11-09 11:22:06,812:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:06,956:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:06,956:INFO:Creating metrics dataframe +2023-11-09 11:22:06,966:INFO:Initializing Gradient Boosting Regressor +2023-11-09 11:22:06,967:INFO:Total runtime is 0.07754165331522624 minutes +2023-11-09 11:22:06,970:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:06,971:INFO:Initializing create_model() +2023-11-09 11:22:06,971:INFO:create_model(self=, estimator=gbr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:06,971:INFO:Checking exceptions +2023-11-09 11:22:06,971:INFO:Importing libraries +2023-11-09 11:22:06,971:INFO:Copying training dataset +2023-11-09 11:22:06,975:INFO:Defining folds +2023-11-09 11:22:06,975:INFO:Declaring metric variables +2023-11-09 11:22:06,978:INFO:Importing untrained model +2023-11-09 11:22:06,982:INFO:Gradient Boosting Regressor Imported successfully +2023-11-09 11:22:06,988:INFO:Starting cross validation +2023-11-09 11:22:06,989:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:07,142:INFO:Calculating mean and std +2023-11-09 11:22:07,144:INFO:Creating metrics dataframe +2023-11-09 11:22:07,147:INFO:Uploading results into container +2023-11-09 11:22:07,148:INFO:Uploading model into container now +2023-11-09 11:22:07,149:INFO:_master_model_container: 16 +2023-11-09 11:22:07,149:INFO:_display_container: 2 +2023-11-09 11:22:07,150:INFO:GradientBoostingRegressor(random_state=123) +2023-11-09 11:22:07,150:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:07,276:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:07,276:INFO:Creating metrics dataframe +2023-11-09 11:22:07,287:INFO:Initializing Light Gradient Boosting Machine +2023-11-09 11:22:07,287:INFO:Total runtime is 0.08287959098815918 minutes +2023-11-09 11:22:07,290:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:07,291:INFO:Initializing create_model() +2023-11-09 11:22:07,291:INFO:create_model(self=, estimator=lightgbm, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:07,291:INFO:Checking exceptions +2023-11-09 11:22:07,291:INFO:Importing libraries +2023-11-09 11:22:07,291:INFO:Copying training dataset +2023-11-09 11:22:07,295:INFO:Defining folds +2023-11-09 11:22:07,295:INFO:Declaring metric variables +2023-11-09 11:22:07,299:INFO:Importing untrained model +2023-11-09 11:22:07,302:INFO:Light Gradient Boosting Machine Imported successfully +2023-11-09 11:22:07,309:INFO:Starting cross validation +2023-11-09 11:22:07,311:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:07,448:INFO:Calculating mean and std +2023-11-09 11:22:07,449:INFO:Creating metrics dataframe +2023-11-09 11:22:07,453:INFO:Uploading results into container +2023-11-09 11:22:07,454:INFO:Uploading model into container now +2023-11-09 11:22:07,454:INFO:_master_model_container: 17 +2023-11-09 11:22:07,454:INFO:_display_container: 2 +2023-11-09 11:22:07,455:INFO:LGBMRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:22:07,455:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:07,586:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:07,586:INFO:Creating metrics dataframe +2023-11-09 11:22:07,597:INFO:Initializing Dummy Regressor +2023-11-09 11:22:07,597:INFO:Total runtime is 0.08804859320322672 minutes +2023-11-09 11:22:07,601:INFO:SubProcess create_model() called ================================== +2023-11-09 11:22:07,601:INFO:Initializing create_model() +2023-11-09 11:22:07,601:INFO:create_model(self=, estimator=dummy, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:07,601:INFO:Checking exceptions +2023-11-09 11:22:07,601:INFO:Importing libraries +2023-11-09 11:22:07,601:INFO:Copying training dataset +2023-11-09 11:22:07,606:INFO:Defining folds +2023-11-09 11:22:07,606:INFO:Declaring metric variables +2023-11-09 11:22:07,609:INFO:Importing untrained model +2023-11-09 11:22:07,612:INFO:Dummy Regressor Imported successfully +2023-11-09 11:22:07,618:INFO:Starting cross validation +2023-11-09 11:22:07,620:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:22:07,684:INFO:Calculating mean and std +2023-11-09 11:22:07,684:INFO:Creating metrics dataframe +2023-11-09 11:22:07,687:INFO:Uploading results into container +2023-11-09 11:22:07,688:INFO:Uploading model into container now +2023-11-09 11:22:07,688:INFO:_master_model_container: 18 +2023-11-09 11:22:07,688:INFO:_display_container: 2 +2023-11-09 11:22:07,688:INFO:DummyRegressor() +2023-11-09 11:22:07,688:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:07,820:INFO:SubProcess create_model() end ================================== +2023-11-09 11:22:07,820:INFO:Creating metrics dataframe +2023-11-09 11:22:07,839:INFO:Initializing create_model() +2023-11-09 11:22:07,840:INFO:create_model(self=, estimator=HuberRegressor(), fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=False, predict=False, fit_kwargs={}, groups=None, refit=True, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=None, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:22:07,840:INFO:Checking exceptions +2023-11-09 11:22:07,841:INFO:Importing libraries +2023-11-09 11:22:07,841:INFO:Copying training dataset +2023-11-09 11:22:07,845:INFO:Defining folds +2023-11-09 11:22:07,845:INFO:Declaring metric variables +2023-11-09 11:22:07,845:INFO:Importing untrained model +2023-11-09 11:22:07,845:INFO:Declaring custom model +2023-11-09 11:22:07,846:INFO:Huber Regressor Imported successfully +2023-11-09 11:22:07,847:INFO:Cross validation set to False +2023-11-09 11:22:07,847:INFO:Fitting Model +2023-11-09 11:22:07,874:INFO:HuberRegressor() +2023-11-09 11:22:07,874:INFO:create_model() successfully completed...................................... +2023-11-09 11:22:08,029:INFO:_master_model_container: 18 +2023-11-09 11:22:08,029:INFO:_display_container: 2 +2023-11-09 11:22:08,029:INFO:HuberRegressor() +2023-11-09 11:22:08,029:INFO:compare_models() successfully completed...................................... +2023-11-09 11:22:08,207:INFO:Initializing predict_model() +2023-11-09 11:22:08,208:INFO:predict_model(self=, estimator=HuberRegressor(), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=.encode_labels at 0x7fbb2cc74280>) +2023-11-09 11:22:08,208:INFO:Checking exceptions +2023-11-09 11:22:08,208:INFO:Preloading libraries +2023-11-09 11:22:08,211:INFO:Set up data. +2023-11-09 11:22:08,215:INFO:Set up index. +2023-11-09 11:22:08,741:WARNING:/tmp/ipykernel_54540/1311405278.py:1: SettingWithCopyWarning: + + +A value is trying to be set on a copy of a slice from a DataFrame + +See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy + + +2023-11-09 11:27:53,909:INFO:PyCaret RegressionExperiment +2023-11-09 11:27:53,909:INFO:Logging name: reg-default-name +2023-11-09 11:27:53,909:INFO:ML Usecase: MLUsecase.REGRESSION +2023-11-09 11:27:53,909:INFO:version 3.1.0 +2023-11-09 11:27:53,909:INFO:Initializing setup() +2023-11-09 11:27:53,909:INFO:self.USI: 8600 +2023-11-09 11:27:53,909:INFO:self._variable_keys: {'seed', 'idx', 'transform_target_param', 'gpu_param', 'target_param', 'log_plots_param', 'pipeline', 'logging_param', 'fold_groups_param', '_ml_usecase', 'html_param', 'gpu_n_jobs_param', 'y', 'y_test', 'y_train', 'memory', 'exp_id', 'X_test', 'exp_name_log', 'USI', 'data', 'X_train', 'fold_shuffle_param', 'X', 'fold_generator', 'n_jobs_param', '_available_plots'} +2023-11-09 11:27:53,909:INFO:Checking environment +2023-11-09 11:27:53,909:INFO:python_version: 3.8.18 +2023-11-09 11:27:53,910:INFO:python_build: ('default', 'Sep 11 2023 13:40:15') +2023-11-09 11:27:53,910:INFO:machine: x86_64 +2023-11-09 11:27:53,910:INFO:platform: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:27:53,910:INFO:Memory: svmem(total=8315187200, available=4863262720, percent=41.5, used=3117289472, free=502550528, active=1476341760, inactive=5498253312, buffers=339787776, cached=4355559424, shared=4476928, slab=650907648) +2023-11-09 11:27:53,910:INFO:Physical Core: 1 +2023-11-09 11:27:53,910:INFO:Logical Core: 2 +2023-11-09 11:27:53,910:INFO:Checking libraries +2023-11-09 11:27:53,910:INFO:System: +2023-11-09 11:27:53,910:INFO: python: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] +2023-11-09 11:27:53,910:INFO:executable: /workspaces/D2I-Jupyter-Notebook-Tools/.conda/bin/python +2023-11-09 11:27:53,910:INFO: machine: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:27:53,911:INFO:PyCaret required dependencies: +2023-11-09 11:27:53,911:INFO: pip: 23.3 +2023-11-09 11:27:53,911:INFO: setuptools: 68.0.0 +2023-11-09 11:27:53,911:INFO: pycaret: 3.1.0 +2023-11-09 11:27:53,911:INFO: IPython: 8.12.0 +2023-11-09 11:27:53,911:INFO: ipywidgets: 8.1.1 +2023-11-09 11:27:53,911:INFO: tqdm: 4.66.1 +2023-11-09 11:27:53,911:INFO: numpy: 1.23.5 +2023-11-09 11:27:53,911:INFO: pandas: 1.5.3 +2023-11-09 11:27:53,911:INFO: jinja2: 3.1.2 +2023-11-09 11:27:53,911:INFO: scipy: 1.10.1 +2023-11-09 11:27:53,911:INFO: joblib: 1.3.2 +2023-11-09 11:27:53,911:INFO: sklearn: 1.2.2 +2023-11-09 11:27:53,911:INFO: pyod: 1.1.1 +2023-11-09 11:27:53,911:INFO: imblearn: 0.11.0 +2023-11-09 11:27:53,911:INFO: category_encoders: 2.6.3 +2023-11-09 11:27:53,912:INFO: lightgbm: 4.1.0 +2023-11-09 11:27:53,912:INFO: numba: 0.58.1 +2023-11-09 11:27:53,912:INFO: requests: 2.31.0 +2023-11-09 11:27:53,912:INFO: matplotlib: 3.7.3 +2023-11-09 11:27:53,912:INFO: scikitplot: 0.3.7 +2023-11-09 11:27:53,912:INFO: yellowbrick: 1.5 +2023-11-09 11:27:53,912:INFO: plotly: 5.18.0 +2023-11-09 11:27:53,912:INFO: plotly-resampler: Not installed +2023-11-09 11:27:53,912:INFO: kaleido: 0.2.1 +2023-11-09 11:27:53,912:INFO: schemdraw: 0.15 +2023-11-09 11:27:53,912:INFO: statsmodels: 0.14.0 +2023-11-09 11:27:53,912:INFO: sktime: 0.21.1 +2023-11-09 11:27:53,912:INFO: tbats: 1.1.3 +2023-11-09 11:27:53,912:INFO: pmdarima: 2.0.4 +2023-11-09 11:27:53,912:INFO: psutil: 5.9.0 +2023-11-09 11:27:53,912:INFO: markupsafe: 2.1.3 +2023-11-09 11:27:53,912:INFO: pickle5: Not installed +2023-11-09 11:27:53,913:INFO: cloudpickle: 3.0.0 +2023-11-09 11:27:53,913:INFO: deprecation: 2.1.0 +2023-11-09 11:27:53,913:INFO: xxhash: 3.4.1 +2023-11-09 11:27:53,913:INFO: wurlitzer: 3.0.3 +2023-11-09 11:27:53,913:INFO:PyCaret optional dependencies: +2023-11-09 11:27:53,913:INFO: shap: Not installed +2023-11-09 11:27:53,913:INFO: interpret: Not installed +2023-11-09 11:27:53,913:INFO: umap: Not installed +2023-11-09 11:27:53,913:INFO: ydata_profiling: Not installed +2023-11-09 11:27:53,913:INFO: explainerdashboard: Not installed +2023-11-09 11:27:53,913:INFO: autoviz: Not installed +2023-11-09 11:27:53,913:INFO: fairlearn: Not installed +2023-11-09 11:27:53,913:INFO: deepchecks: Not installed +2023-11-09 11:27:53,913:INFO: xgboost: Not installed +2023-11-09 11:27:53,913:INFO: catboost: Not installed +2023-11-09 11:27:53,913:INFO: kmodes: Not installed +2023-11-09 11:27:53,913:INFO: mlxtend: Not installed +2023-11-09 11:27:53,913:INFO: statsforecast: Not installed +2023-11-09 11:27:53,913:INFO: tune_sklearn: Not installed +2023-11-09 11:27:53,914:INFO: ray: Not installed +2023-11-09 11:27:53,914:INFO: hyperopt: Not installed +2023-11-09 11:27:53,914:INFO: optuna: Not installed +2023-11-09 11:27:53,914:INFO: skopt: Not installed +2023-11-09 11:27:53,914:INFO: mlflow: Not installed +2023-11-09 11:27:53,914:INFO: gradio: Not installed +2023-11-09 11:27:53,914:INFO: fastapi: Not installed +2023-11-09 11:27:53,914:INFO: uvicorn: Not installed +2023-11-09 11:27:53,914:INFO: m2cgen: Not installed +2023-11-09 11:27:53,914:INFO: evidently: Not installed +2023-11-09 11:27:53,914:INFO: fugue: Not installed +2023-11-09 11:27:53,914:INFO: streamlit: Not installed +2023-11-09 11:27:53,914:INFO: prophet: Not installed +2023-11-09 11:27:53,914:INFO:None +2023-11-09 11:27:53,914:INFO:Set up data. +2023-11-09 11:27:53,918:INFO:Set up folding strategy. +2023-11-09 11:27:53,918:INFO:Set up train/test split. +2023-11-09 11:27:53,918:INFO:Set up data. +2023-11-09 11:27:53,921:INFO:Set up index. +2023-11-09 11:27:53,922:INFO:Assigning column types. +2023-11-09 11:27:53,924:INFO:Engine successfully changes for model 'lr' to 'sklearn'. +2023-11-09 11:27:53,924:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:27:53,928:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:27:53,932:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:27:53,989:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,027:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,028:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,028:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,029:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,033:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,037:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,086:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,124:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,124:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,125:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,125:INFO:Engine successfully changes for model 'lasso' to 'sklearn'. +2023-11-09 11:27:54,129:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,133:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,181:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,218:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,219:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,219:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,223:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,227:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,273:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,313:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,314:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,314:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,314:INFO:Engine successfully changes for model 'ridge' to 'sklearn'. +2023-11-09 11:27:54,322:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,370:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,407:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,408:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,408:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,416:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,466:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,504:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,505:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,505:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,506:INFO:Engine successfully changes for model 'en' to 'sklearn'. +2023-11-09 11:27:54,569:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,614:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,614:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,615:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,673:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,711:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,712:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,712:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,712:INFO:Engine successfully changes for model 'knn' to 'sklearn'. +2023-11-09 11:27:54,768:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,808:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,808:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,863:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:27:54,901:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,902:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:54,902:INFO:Engine successfully changes for model 'svm' to 'sklearn'. +2023-11-09 11:27:55,028:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:55,028:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:55,177:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:55,177:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:55,178:INFO:Preparing preprocessing pipeline... +2023-11-09 11:27:55,178:INFO:Set up target transformation. +2023-11-09 11:27:55,178:INFO:Set up simple imputation. +2023-11-09 11:27:55,179:INFO:Set up column name cleaning. +2023-11-09 11:27:55,210:INFO:Finished creating preprocessing pipeline. +2023-11-09 11:27:55,219:INFO:Pipeline: Pipeline(memory=FastMemory(location=/tmp/joblib), + steps=[('target_transformation', + TransformerWrapperWithInverse(transformer=TargetTransformer(estimator=PowerTransformer(standardize=False)))), + ('numerical_imputer', + TransformerWrapper(include=['Year', 'Series'], + transformer=SimpleImputer())), + ('categorical_imputer', + TransformerWrapper(include=[], + transformer=SimpleImputer(strategy='most_frequent'))), + ('clean_column_names', + TransformerWrapper(transformer=CleanColumnNames()))]) +2023-11-09 11:27:55,219:INFO:Creating final display dataframe. +2023-11-09 11:27:55,297:INFO:Setup _display_container: Description Value +0 Session id 123 +1 Target Average price All property types +2 Target type Regression +3 Original data shape (523, 4) +4 Transformed data shape (523, 4) +5 Transformed train set shape (372, 4) +6 Transformed test set shape (151, 4) +7 Numeric features 2 +8 Preprocess True +9 Imputation type simple +10 Numeric imputation mean +11 Categorical imputation mode +12 Transform target True +13 Transform target method yeo-johnson +14 Fold Generator TimeSeriesSplit +15 Fold Number 3 +16 CPU Jobs -1 +17 Use GPU False +18 Log Experiment False +19 Experiment Name reg-default-name +20 USI 8600 +2023-11-09 11:27:55,399:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:55,399:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:55,561:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:55,562:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:27:55,563:INFO:setup() successfully completed in 1.66s............... +2023-11-09 11:27:55,649:INFO:Initializing compare_models() +2023-11-09 11:27:55,652:INFO:compare_models(self=, include=None, fold=None, round=4, cross_validation=True, sort=MAE, n_select=1, budget_time=None, turbo=True, errors=ignore, fit_kwargs=None, groups=None, experiment_custom_tags=None, probability_threshold=None, verbose=True, parallel=None, caller_params={'self': , 'include': None, 'exclude': None, 'fold': None, 'round': 4, 'cross_validation': True, 'sort': 'MAE', 'n_select': 1, 'budget_time': None, 'turbo': True, 'errors': 'ignore', 'fit_kwargs': None, 'groups': None, 'experiment_custom_tags': None, 'engine': None, 'verbose': True, 'parallel': None, '__class__': }, exclude=None) +2023-11-09 11:27:55,652:INFO:Checking exceptions +2023-11-09 11:27:55,654:INFO:Preparing display monitor +2023-11-09 11:27:55,680:INFO:Initializing Linear Regression +2023-11-09 11:27:55,680:INFO:Total runtime is 5.527337392171224e-06 minutes +2023-11-09 11:27:55,683:INFO:SubProcess create_model() called ================================== +2023-11-09 11:27:55,684:INFO:Initializing create_model() +2023-11-09 11:27:55,684:INFO:create_model(self=, estimator=lr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:27:55,684:INFO:Checking exceptions +2023-11-09 11:27:55,684:INFO:Importing libraries +2023-11-09 11:27:55,684:INFO:Copying training dataset +2023-11-09 11:27:55,687:INFO:Defining folds +2023-11-09 11:27:55,687:INFO:Declaring metric variables +2023-11-09 11:27:55,690:INFO:Importing untrained model +2023-11-09 11:27:55,694:INFO:Linear Regression Imported successfully +2023-11-09 11:27:55,699:INFO:Starting cross validation +2023-11-09 11:27:55,700:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:27:57,529:INFO:Calculating mean and std +2023-11-09 11:27:57,531:INFO:Creating metrics dataframe +2023-11-09 11:27:57,535:INFO:Uploading results into container +2023-11-09 11:27:57,536:INFO:Uploading model into container now +2023-11-09 11:27:57,536:INFO:_master_model_container: 1 +2023-11-09 11:27:57,537:INFO:_display_container: 2 +2023-11-09 11:27:57,537:INFO:LinearRegression(n_jobs=-1) +2023-11-09 11:27:57,537:INFO:create_model() successfully completed...................................... +2023-11-09 11:27:57,688:INFO:SubProcess create_model() end ================================== +2023-11-09 11:27:57,688:INFO:Creating metrics dataframe +2023-11-09 11:27:57,696:INFO:Initializing Lasso Regression +2023-11-09 11:27:57,697:INFO:Total runtime is 0.03361747662226359 minutes +2023-11-09 11:27:57,700:INFO:SubProcess create_model() called ================================== +2023-11-09 11:27:57,701:INFO:Initializing create_model() +2023-11-09 11:27:57,701:INFO:create_model(self=, estimator=lasso, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:27:57,701:INFO:Checking exceptions +2023-11-09 11:27:57,701:INFO:Importing libraries +2023-11-09 11:27:57,701:INFO:Copying training dataset +2023-11-09 11:27:57,705:INFO:Defining folds +2023-11-09 11:27:57,705:INFO:Declaring metric variables +2023-11-09 11:27:57,709:INFO:Importing untrained model +2023-11-09 11:27:57,712:INFO:Lasso Regression Imported successfully +2023-11-09 11:27:57,719:INFO:Starting cross validation +2023-11-09 11:27:57,720:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:27:57,813:INFO:Calculating mean and std +2023-11-09 11:27:57,815:INFO:Creating metrics dataframe +2023-11-09 11:27:57,826:INFO:Uploading results into container +2023-11-09 11:27:57,827:INFO:Uploading model into container now +2023-11-09 11:27:57,828:INFO:_master_model_container: 2 +2023-11-09 11:27:57,828:INFO:_display_container: 2 +2023-11-09 11:27:57,828:INFO:Lasso(random_state=123) +2023-11-09 11:27:57,828:INFO:create_model() successfully completed...................................... +2023-11-09 11:27:57,967:INFO:SubProcess create_model() end ================================== +2023-11-09 11:27:57,967:INFO:Creating metrics dataframe +2023-11-09 11:27:57,978:INFO:Initializing Ridge Regression +2023-11-09 11:27:57,978:INFO:Total runtime is 0.03830134073893229 minutes +2023-11-09 11:27:57,981:INFO:SubProcess create_model() called ================================== +2023-11-09 11:27:57,981:INFO:Initializing create_model() +2023-11-09 11:27:57,981:INFO:create_model(self=, estimator=ridge, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:27:57,981:INFO:Checking exceptions +2023-11-09 11:27:57,981:INFO:Importing libraries +2023-11-09 11:27:57,981:INFO:Copying training dataset +2023-11-09 11:27:57,985:INFO:Defining folds +2023-11-09 11:27:57,985:INFO:Declaring metric variables +2023-11-09 11:27:57,989:INFO:Importing untrained model +2023-11-09 11:27:57,993:INFO:Ridge Regression Imported successfully +2023-11-09 11:27:58,004:INFO:Starting cross validation +2023-11-09 11:27:58,005:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:27:58,117:INFO:Calculating mean and std +2023-11-09 11:27:58,119:INFO:Creating metrics dataframe +2023-11-09 11:27:58,123:INFO:Uploading results into container +2023-11-09 11:27:58,124:INFO:Uploading model into container now +2023-11-09 11:27:58,124:INFO:_master_model_container: 3 +2023-11-09 11:27:58,124:INFO:_display_container: 2 +2023-11-09 11:27:58,124:INFO:Ridge(random_state=123) +2023-11-09 11:27:58,124:INFO:create_model() successfully completed...................................... +2023-11-09 11:27:58,244:INFO:SubProcess create_model() end ================================== +2023-11-09 11:27:58,245:INFO:Creating metrics dataframe +2023-11-09 11:27:58,253:INFO:Initializing Elastic Net +2023-11-09 11:27:58,253:INFO:Total runtime is 0.04289503494898478 minutes +2023-11-09 11:27:58,257:INFO:SubProcess create_model() called ================================== +2023-11-09 11:27:58,257:INFO:Initializing create_model() +2023-11-09 11:27:58,257:INFO:create_model(self=, estimator=en, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:27:58,257:INFO:Checking exceptions +2023-11-09 11:27:58,257:INFO:Importing libraries +2023-11-09 11:27:58,257:INFO:Copying training dataset +2023-11-09 11:27:58,261:INFO:Defining folds +2023-11-09 11:27:58,261:INFO:Declaring metric variables +2023-11-09 11:27:58,264:INFO:Importing untrained model +2023-11-09 11:27:58,268:INFO:Elastic Net Imported successfully +2023-11-09 11:27:58,274:INFO:Starting cross validation +2023-11-09 11:27:58,275:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:27:58,355:INFO:Calculating mean and std +2023-11-09 11:27:58,355:INFO:Creating metrics dataframe +2023-11-09 11:27:58,358:INFO:Uploading results into container +2023-11-09 11:27:58,358:INFO:Uploading model into container now +2023-11-09 11:27:58,359:INFO:_master_model_container: 4 +2023-11-09 11:27:58,359:INFO:_display_container: 2 +2023-11-09 11:27:58,359:INFO:ElasticNet(random_state=123) +2023-11-09 11:27:58,359:INFO:create_model() successfully completed...................................... +2023-11-09 11:27:58,480:INFO:SubProcess create_model() end ================================== +2023-11-09 11:27:58,480:INFO:Creating metrics dataframe +2023-11-09 11:27:58,493:INFO:Initializing Least Angle Regression +2023-11-09 11:27:58,493:INFO:Total runtime is 0.046884330113728834 minutes +2023-11-09 11:27:58,497:INFO:SubProcess create_model() called ================================== +2023-11-09 11:27:58,497:INFO:Initializing create_model() +2023-11-09 11:27:58,497:INFO:create_model(self=, estimator=lar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:27:58,497:INFO:Checking exceptions +2023-11-09 11:27:58,498:INFO:Importing libraries +2023-11-09 11:27:58,498:INFO:Copying training dataset +2023-11-09 11:27:58,503:INFO:Defining folds +2023-11-09 11:27:58,503:INFO:Declaring metric variables +2023-11-09 11:27:58,508:INFO:Importing untrained model +2023-11-09 11:27:58,513:INFO:Least Angle Regression Imported successfully +2023-11-09 11:27:58,521:INFO:Starting cross validation +2023-11-09 11:27:58,523:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:27:58,684:INFO:Calculating mean and std +2023-11-09 11:27:58,686:INFO:Creating metrics dataframe +2023-11-09 11:27:58,689:INFO:Uploading results into container +2023-11-09 11:27:58,690:INFO:Uploading model into container now +2023-11-09 11:27:58,690:INFO:_master_model_container: 5 +2023-11-09 11:27:58,690:INFO:_display_container: 2 +2023-11-09 11:27:58,691:INFO:Lars(random_state=123) +2023-11-09 11:27:58,691:INFO:create_model() successfully completed...................................... +2023-11-09 11:27:58,831:INFO:SubProcess create_model() end ================================== +2023-11-09 11:27:58,831:INFO:Creating metrics dataframe +2023-11-09 11:27:58,841:INFO:Initializing Lasso Least Angle Regression +2023-11-09 11:27:58,841:INFO:Total runtime is 0.05269551277160644 minutes +2023-11-09 11:27:58,845:INFO:SubProcess create_model() called ================================== +2023-11-09 11:27:58,845:INFO:Initializing create_model() +2023-11-09 11:27:58,845:INFO:create_model(self=, estimator=llar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:27:58,846:INFO:Checking exceptions +2023-11-09 11:27:58,846:INFO:Importing libraries +2023-11-09 11:27:58,846:INFO:Copying training dataset +2023-11-09 11:27:58,849:INFO:Defining folds +2023-11-09 11:27:58,849:INFO:Declaring metric variables +2023-11-09 11:27:58,852:INFO:Importing untrained model +2023-11-09 11:27:58,856:INFO:Lasso Least Angle Regression Imported successfully +2023-11-09 11:27:58,862:INFO:Starting cross validation +2023-11-09 11:27:58,863:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:27:58,938:INFO:Calculating mean and std +2023-11-09 11:27:58,939:INFO:Creating metrics dataframe +2023-11-09 11:27:58,942:INFO:Uploading results into container +2023-11-09 11:27:58,942:INFO:Uploading model into container now +2023-11-09 11:27:58,942:INFO:_master_model_container: 6 +2023-11-09 11:27:58,942:INFO:_display_container: 2 +2023-11-09 11:27:58,943:INFO:LassoLars(random_state=123) +2023-11-09 11:27:58,943:INFO:create_model() successfully completed...................................... +2023-11-09 11:27:59,068:INFO:SubProcess create_model() end ================================== +2023-11-09 11:27:59,068:INFO:Creating metrics dataframe +2023-11-09 11:27:59,077:INFO:Initializing Orthogonal Matching Pursuit +2023-11-09 11:27:59,078:INFO:Total runtime is 0.05663313468297322 minutes +2023-11-09 11:27:59,081:INFO:SubProcess create_model() called ================================== +2023-11-09 11:27:59,081:INFO:Initializing create_model() +2023-11-09 11:27:59,081:INFO:create_model(self=, estimator=omp, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:27:59,082:INFO:Checking exceptions +2023-11-09 11:27:59,082:INFO:Importing libraries +2023-11-09 11:27:59,082:INFO:Copying training dataset +2023-11-09 11:27:59,085:INFO:Defining folds +2023-11-09 11:27:59,085:INFO:Declaring metric variables +2023-11-09 11:27:59,088:INFO:Importing untrained model +2023-11-09 11:27:59,092:INFO:Orthogonal Matching Pursuit Imported successfully +2023-11-09 11:27:59,097:INFO:Starting cross validation +2023-11-09 11:27:59,098:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:27:59,173:INFO:Calculating mean and std +2023-11-09 11:27:59,173:INFO:Creating metrics dataframe +2023-11-09 11:27:59,178:INFO:Uploading results into container +2023-11-09 11:27:59,178:INFO:Uploading model into container now +2023-11-09 11:27:59,179:INFO:_master_model_container: 7 +2023-11-09 11:27:59,179:INFO:_display_container: 2 +2023-11-09 11:27:59,179:INFO:OrthogonalMatchingPursuit() +2023-11-09 11:27:59,179:INFO:create_model() successfully completed...................................... +2023-11-09 11:27:59,300:INFO:SubProcess create_model() end ================================== +2023-11-09 11:27:59,300:INFO:Creating metrics dataframe +2023-11-09 11:27:59,310:INFO:Initializing Bayesian Ridge +2023-11-09 11:27:59,310:INFO:Total runtime is 0.06050433715184529 minutes +2023-11-09 11:27:59,314:INFO:SubProcess create_model() called ================================== +2023-11-09 11:27:59,314:INFO:Initializing create_model() +2023-11-09 11:27:59,314:INFO:create_model(self=, estimator=br, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:27:59,314:INFO:Checking exceptions +2023-11-09 11:27:59,314:INFO:Importing libraries +2023-11-09 11:27:59,315:INFO:Copying training dataset +2023-11-09 11:27:59,318:INFO:Defining folds +2023-11-09 11:27:59,318:INFO:Declaring metric variables +2023-11-09 11:27:59,321:INFO:Importing untrained model +2023-11-09 11:27:59,324:INFO:Bayesian Ridge Imported successfully +2023-11-09 11:27:59,330:INFO:Starting cross validation +2023-11-09 11:27:59,332:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:27:59,407:INFO:Calculating mean and std +2023-11-09 11:27:59,408:INFO:Creating metrics dataframe +2023-11-09 11:27:59,410:INFO:Uploading results into container +2023-11-09 11:27:59,411:INFO:Uploading model into container now +2023-11-09 11:27:59,411:INFO:_master_model_container: 8 +2023-11-09 11:27:59,411:INFO:_display_container: 2 +2023-11-09 11:27:59,412:INFO:BayesianRidge() +2023-11-09 11:27:59,412:INFO:create_model() successfully completed...................................... +2023-11-09 11:27:59,538:INFO:SubProcess create_model() end ================================== +2023-11-09 11:27:59,538:INFO:Creating metrics dataframe +2023-11-09 11:27:59,547:INFO:Initializing Passive Aggressive Regressor +2023-11-09 11:27:59,547:INFO:Total runtime is 0.06446006298065185 minutes +2023-11-09 11:27:59,551:INFO:SubProcess create_model() called ================================== +2023-11-09 11:27:59,551:INFO:Initializing create_model() +2023-11-09 11:27:59,551:INFO:create_model(self=, estimator=par, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:27:59,551:INFO:Checking exceptions +2023-11-09 11:27:59,552:INFO:Importing libraries +2023-11-09 11:27:59,552:INFO:Copying training dataset +2023-11-09 11:27:59,555:INFO:Defining folds +2023-11-09 11:27:59,555:INFO:Declaring metric variables +2023-11-09 11:27:59,559:INFO:Importing untrained model +2023-11-09 11:27:59,562:INFO:Passive Aggressive Regressor Imported successfully +2023-11-09 11:27:59,568:INFO:Starting cross validation +2023-11-09 11:27:59,569:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:27:59,651:INFO:Calculating mean and std +2023-11-09 11:27:59,652:INFO:Creating metrics dataframe +2023-11-09 11:27:59,656:INFO:Uploading results into container +2023-11-09 11:27:59,656:INFO:Uploading model into container now +2023-11-09 11:27:59,657:INFO:_master_model_container: 9 +2023-11-09 11:27:59,657:INFO:_display_container: 2 +2023-11-09 11:27:59,657:INFO:PassiveAggressiveRegressor(random_state=123) +2023-11-09 11:27:59,657:INFO:create_model() successfully completed...................................... +2023-11-09 11:27:59,785:INFO:SubProcess create_model() end ================================== +2023-11-09 11:27:59,785:INFO:Creating metrics dataframe +2023-11-09 11:27:59,795:INFO:Initializing Huber Regressor +2023-11-09 11:27:59,795:INFO:Total runtime is 0.06858917872111002 minutes +2023-11-09 11:27:59,798:INFO:SubProcess create_model() called ================================== +2023-11-09 11:27:59,799:INFO:Initializing create_model() +2023-11-09 11:27:59,799:INFO:create_model(self=, estimator=huber, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:27:59,799:INFO:Checking exceptions +2023-11-09 11:27:59,799:INFO:Importing libraries +2023-11-09 11:27:59,799:INFO:Copying training dataset +2023-11-09 11:27:59,802:INFO:Defining folds +2023-11-09 11:27:59,803:INFO:Declaring metric variables +2023-11-09 11:27:59,805:INFO:Importing untrained model +2023-11-09 11:27:59,808:INFO:Huber Regressor Imported successfully +2023-11-09 11:27:59,814:INFO:Starting cross validation +2023-11-09 11:27:59,815:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:27:59,930:INFO:Calculating mean and std +2023-11-09 11:27:59,932:INFO:Creating metrics dataframe +2023-11-09 11:27:59,935:INFO:Uploading results into container +2023-11-09 11:27:59,937:INFO:Uploading model into container now +2023-11-09 11:27:59,937:INFO:_master_model_container: 10 +2023-11-09 11:27:59,937:INFO:_display_container: 2 +2023-11-09 11:27:59,938:INFO:HuberRegressor() +2023-11-09 11:27:59,938:INFO:create_model() successfully completed...................................... +2023-11-09 11:28:00,059:INFO:SubProcess create_model() end ================================== +2023-11-09 11:28:00,060:INFO:Creating metrics dataframe +2023-11-09 11:28:00,069:INFO:Initializing K Neighbors Regressor +2023-11-09 11:28:00,069:INFO:Total runtime is 0.07316226164499919 minutes +2023-11-09 11:28:00,073:INFO:SubProcess create_model() called ================================== +2023-11-09 11:28:00,073:INFO:Initializing create_model() +2023-11-09 11:28:00,074:INFO:create_model(self=, estimator=knn, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:28:00,074:INFO:Checking exceptions +2023-11-09 11:28:00,074:INFO:Importing libraries +2023-11-09 11:28:00,074:INFO:Copying training dataset +2023-11-09 11:28:00,077:INFO:Defining folds +2023-11-09 11:28:00,077:INFO:Declaring metric variables +2023-11-09 11:28:00,081:INFO:Importing untrained model +2023-11-09 11:28:00,084:INFO:K Neighbors Regressor Imported successfully +2023-11-09 11:28:00,089:INFO:Starting cross validation +2023-11-09 11:28:00,090:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:28:00,215:INFO:Calculating mean and std +2023-11-09 11:28:00,217:INFO:Creating metrics dataframe +2023-11-09 11:28:00,220:INFO:Uploading results into container +2023-11-09 11:28:00,223:INFO:Uploading model into container now +2023-11-09 11:28:00,224:INFO:_master_model_container: 11 +2023-11-09 11:28:00,224:INFO:_display_container: 2 +2023-11-09 11:28:00,224:INFO:KNeighborsRegressor(n_jobs=-1) +2023-11-09 11:28:00,224:INFO:create_model() successfully completed...................................... +2023-11-09 11:28:00,363:INFO:SubProcess create_model() end ================================== +2023-11-09 11:28:00,363:INFO:Creating metrics dataframe +2023-11-09 11:28:00,374:INFO:Initializing Decision Tree Regressor +2023-11-09 11:28:00,374:INFO:Total runtime is 0.0782459537188212 minutes +2023-11-09 11:28:00,378:INFO:SubProcess create_model() called ================================== +2023-11-09 11:28:00,378:INFO:Initializing create_model() +2023-11-09 11:28:00,378:INFO:create_model(self=, estimator=dt, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:28:00,378:INFO:Checking exceptions +2023-11-09 11:28:00,379:INFO:Importing libraries +2023-11-09 11:28:00,379:INFO:Copying training dataset +2023-11-09 11:28:00,382:INFO:Defining folds +2023-11-09 11:28:00,382:INFO:Declaring metric variables +2023-11-09 11:28:00,385:INFO:Importing untrained model +2023-11-09 11:28:00,389:INFO:Decision Tree Regressor Imported successfully +2023-11-09 11:28:00,397:INFO:Starting cross validation +2023-11-09 11:28:00,404:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:28:00,524:INFO:Calculating mean and std +2023-11-09 11:28:00,527:INFO:Creating metrics dataframe +2023-11-09 11:28:00,532:INFO:Uploading results into container +2023-11-09 11:28:00,532:INFO:Uploading model into container now +2023-11-09 11:28:00,533:INFO:_master_model_container: 12 +2023-11-09 11:28:00,533:INFO:_display_container: 2 +2023-11-09 11:28:00,533:INFO:DecisionTreeRegressor(random_state=123) +2023-11-09 11:28:00,534:INFO:create_model() successfully completed...................................... +2023-11-09 11:28:00,682:INFO:SubProcess create_model() end ================================== +2023-11-09 11:28:00,682:INFO:Creating metrics dataframe +2023-11-09 11:28:00,698:INFO:Initializing Random Forest Regressor +2023-11-09 11:28:00,700:INFO:Total runtime is 0.08367493152618408 minutes +2023-11-09 11:28:00,705:INFO:SubProcess create_model() called ================================== +2023-11-09 11:28:00,706:INFO:Initializing create_model() +2023-11-09 11:28:00,706:INFO:create_model(self=, estimator=rf, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:28:00,707:INFO:Checking exceptions +2023-11-09 11:28:00,707:INFO:Importing libraries +2023-11-09 11:28:00,707:INFO:Copying training dataset +2023-11-09 11:28:00,713:INFO:Defining folds +2023-11-09 11:28:00,716:INFO:Declaring metric variables +2023-11-09 11:28:00,727:INFO:Importing untrained model +2023-11-09 11:28:00,733:INFO:Random Forest Regressor Imported successfully +2023-11-09 11:28:00,743:INFO:Starting cross validation +2023-11-09 11:28:00,744:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:28:01,175:INFO:Calculating mean and std +2023-11-09 11:28:01,176:INFO:Creating metrics dataframe +2023-11-09 11:28:01,180:INFO:Uploading results into container +2023-11-09 11:28:01,181:INFO:Uploading model into container now +2023-11-09 11:28:01,181:INFO:_master_model_container: 13 +2023-11-09 11:28:01,181:INFO:_display_container: 2 +2023-11-09 11:28:01,181:INFO:RandomForestRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:28:01,182:INFO:create_model() successfully completed...................................... +2023-11-09 11:28:01,304:INFO:SubProcess create_model() end ================================== +2023-11-09 11:28:01,305:INFO:Creating metrics dataframe +2023-11-09 11:28:01,315:INFO:Initializing Extra Trees Regressor +2023-11-09 11:28:01,316:INFO:Total runtime is 0.0939310352007548 minutes +2023-11-09 11:28:01,319:INFO:SubProcess create_model() called ================================== +2023-11-09 11:28:01,319:INFO:Initializing create_model() +2023-11-09 11:28:01,319:INFO:create_model(self=, estimator=et, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:28:01,320:INFO:Checking exceptions +2023-11-09 11:28:01,320:INFO:Importing libraries +2023-11-09 11:28:01,320:INFO:Copying training dataset +2023-11-09 11:28:01,323:INFO:Defining folds +2023-11-09 11:28:01,323:INFO:Declaring metric variables +2023-11-09 11:28:01,327:INFO:Importing untrained model +2023-11-09 11:28:01,330:INFO:Extra Trees Regressor Imported successfully +2023-11-09 11:28:01,337:INFO:Starting cross validation +2023-11-09 11:28:01,338:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:28:01,668:INFO:Calculating mean and std +2023-11-09 11:28:01,669:INFO:Creating metrics dataframe +2023-11-09 11:28:01,672:INFO:Uploading results into container +2023-11-09 11:28:01,673:INFO:Uploading model into container now +2023-11-09 11:28:01,674:INFO:_master_model_container: 14 +2023-11-09 11:28:01,674:INFO:_display_container: 2 +2023-11-09 11:28:01,674:INFO:ExtraTreesRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:28:01,674:INFO:create_model() successfully completed...................................... +2023-11-09 11:28:01,801:INFO:SubProcess create_model() end ================================== +2023-11-09 11:28:01,801:INFO:Creating metrics dataframe +2023-11-09 11:28:01,811:INFO:Initializing AdaBoost Regressor +2023-11-09 11:28:01,812:INFO:Total runtime is 0.10219961404800415 minutes +2023-11-09 11:28:01,815:INFO:SubProcess create_model() called ================================== +2023-11-09 11:28:01,816:INFO:Initializing create_model() +2023-11-09 11:28:01,816:INFO:create_model(self=, estimator=ada, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:28:01,816:INFO:Checking exceptions +2023-11-09 11:28:01,816:INFO:Importing libraries +2023-11-09 11:28:01,816:INFO:Copying training dataset +2023-11-09 11:28:01,819:INFO:Defining folds +2023-11-09 11:28:01,820:INFO:Declaring metric variables +2023-11-09 11:28:01,823:INFO:Importing untrained model +2023-11-09 11:28:01,826:INFO:AdaBoost Regressor Imported successfully +2023-11-09 11:28:01,832:INFO:Starting cross validation +2023-11-09 11:28:01,833:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:28:02,034:INFO:Calculating mean and std +2023-11-09 11:28:02,036:INFO:Creating metrics dataframe +2023-11-09 11:28:02,039:INFO:Uploading results into container +2023-11-09 11:28:02,040:INFO:Uploading model into container now +2023-11-09 11:28:02,040:INFO:_master_model_container: 15 +2023-11-09 11:28:02,040:INFO:_display_container: 2 +2023-11-09 11:28:02,041:INFO:AdaBoostRegressor(random_state=123) +2023-11-09 11:28:02,041:INFO:create_model() successfully completed...................................... +2023-11-09 11:28:02,159:INFO:SubProcess create_model() end ================================== +2023-11-09 11:28:02,159:INFO:Creating metrics dataframe +2023-11-09 11:28:02,170:INFO:Initializing Gradient Boosting Regressor +2023-11-09 11:28:02,170:INFO:Total runtime is 0.10817350546518961 minutes +2023-11-09 11:28:02,174:INFO:SubProcess create_model() called ================================== +2023-11-09 11:28:02,174:INFO:Initializing create_model() +2023-11-09 11:28:02,174:INFO:create_model(self=, estimator=gbr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:28:02,174:INFO:Checking exceptions +2023-11-09 11:28:02,174:INFO:Importing libraries +2023-11-09 11:28:02,174:INFO:Copying training dataset +2023-11-09 11:28:02,178:INFO:Defining folds +2023-11-09 11:28:02,178:INFO:Declaring metric variables +2023-11-09 11:28:02,181:INFO:Importing untrained model +2023-11-09 11:28:02,184:INFO:Gradient Boosting Regressor Imported successfully +2023-11-09 11:28:02,190:INFO:Starting cross validation +2023-11-09 11:28:02,191:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:28:02,378:INFO:Calculating mean and std +2023-11-09 11:28:02,380:INFO:Creating metrics dataframe +2023-11-09 11:28:02,384:INFO:Uploading results into container +2023-11-09 11:28:02,385:INFO:Uploading model into container now +2023-11-09 11:28:02,385:INFO:_master_model_container: 16 +2023-11-09 11:28:02,385:INFO:_display_container: 2 +2023-11-09 11:28:02,386:INFO:GradientBoostingRegressor(random_state=123) +2023-11-09 11:28:02,386:INFO:create_model() successfully completed...................................... +2023-11-09 11:28:02,515:INFO:SubProcess create_model() end ================================== +2023-11-09 11:28:02,515:INFO:Creating metrics dataframe +2023-11-09 11:28:02,527:INFO:Initializing Light Gradient Boosting Machine +2023-11-09 11:28:02,527:INFO:Total runtime is 0.1141239841779073 minutes +2023-11-09 11:28:02,531:INFO:SubProcess create_model() called ================================== +2023-11-09 11:28:02,531:INFO:Initializing create_model() +2023-11-09 11:28:02,531:INFO:create_model(self=, estimator=lightgbm, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:28:02,531:INFO:Checking exceptions +2023-11-09 11:28:02,532:INFO:Importing libraries +2023-11-09 11:28:02,532:INFO:Copying training dataset +2023-11-09 11:28:02,535:INFO:Defining folds +2023-11-09 11:28:02,535:INFO:Declaring metric variables +2023-11-09 11:28:02,539:INFO:Importing untrained model +2023-11-09 11:28:02,542:INFO:Light Gradient Boosting Machine Imported successfully +2023-11-09 11:28:02,548:INFO:Starting cross validation +2023-11-09 11:28:02,550:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:28:02,985:INFO:Calculating mean and std +2023-11-09 11:28:02,986:INFO:Creating metrics dataframe +2023-11-09 11:28:02,989:INFO:Uploading results into container +2023-11-09 11:28:02,990:INFO:Uploading model into container now +2023-11-09 11:28:02,990:INFO:_master_model_container: 17 +2023-11-09 11:28:02,990:INFO:_display_container: 2 +2023-11-09 11:28:02,991:INFO:LGBMRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:28:02,991:INFO:create_model() successfully completed...................................... +2023-11-09 11:28:03,121:INFO:SubProcess create_model() end ================================== +2023-11-09 11:28:03,121:INFO:Creating metrics dataframe +2023-11-09 11:28:03,132:INFO:Initializing Dummy Regressor +2023-11-09 11:28:03,132:INFO:Total runtime is 0.12420696020126341 minutes +2023-11-09 11:28:03,136:INFO:SubProcess create_model() called ================================== +2023-11-09 11:28:03,136:INFO:Initializing create_model() +2023-11-09 11:28:03,136:INFO:create_model(self=, estimator=dummy, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:28:03,136:INFO:Checking exceptions +2023-11-09 11:28:03,136:INFO:Importing libraries +2023-11-09 11:28:03,136:INFO:Copying training dataset +2023-11-09 11:28:03,140:INFO:Defining folds +2023-11-09 11:28:03,140:INFO:Declaring metric variables +2023-11-09 11:28:03,145:INFO:Importing untrained model +2023-11-09 11:28:03,150:INFO:Dummy Regressor Imported successfully +2023-11-09 11:28:03,158:INFO:Starting cross validation +2023-11-09 11:28:03,159:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:28:03,231:INFO:Calculating mean and std +2023-11-09 11:28:03,231:INFO:Creating metrics dataframe +2023-11-09 11:28:03,234:INFO:Uploading results into container +2023-11-09 11:28:03,235:INFO:Uploading model into container now +2023-11-09 11:28:03,235:INFO:_master_model_container: 18 +2023-11-09 11:28:03,235:INFO:_display_container: 2 +2023-11-09 11:28:03,236:INFO:DummyRegressor() +2023-11-09 11:28:03,236:INFO:create_model() successfully completed...................................... +2023-11-09 11:28:03,363:INFO:SubProcess create_model() end ================================== +2023-11-09 11:28:03,363:INFO:Creating metrics dataframe +2023-11-09 11:28:03,383:INFO:Initializing create_model() +2023-11-09 11:28:03,383:INFO:create_model(self=, estimator=HuberRegressor(), fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=False, predict=False, fit_kwargs={}, groups=None, refit=True, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=None, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:28:03,383:INFO:Checking exceptions +2023-11-09 11:28:03,385:INFO:Importing libraries +2023-11-09 11:28:03,385:INFO:Copying training dataset +2023-11-09 11:28:03,388:INFO:Defining folds +2023-11-09 11:28:03,388:INFO:Declaring metric variables +2023-11-09 11:28:03,388:INFO:Importing untrained model +2023-11-09 11:28:03,388:INFO:Declaring custom model +2023-11-09 11:28:03,388:INFO:Huber Regressor Imported successfully +2023-11-09 11:28:03,389:INFO:Cross validation set to False +2023-11-09 11:28:03,389:INFO:Fitting Model +2023-11-09 11:28:03,412:INFO:HuberRegressor() +2023-11-09 11:28:03,413:INFO:create_model() successfully completed...................................... +2023-11-09 11:28:03,575:INFO:_master_model_container: 18 +2023-11-09 11:28:03,576:INFO:_display_container: 2 +2023-11-09 11:28:03,576:INFO:HuberRegressor() +2023-11-09 11:28:03,576:INFO:compare_models() successfully completed...................................... +2023-11-09 11:28:03,756:INFO:Initializing predict_model() +2023-11-09 11:28:03,757:INFO:predict_model(self=, estimator=HuberRegressor(), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=.encode_labels at 0x7fbb2ca584c0>) +2023-11-09 11:28:03,757:INFO:Checking exceptions +2023-11-09 11:28:03,757:INFO:Preloading libraries +2023-11-09 11:28:03,759:INFO:Set up data. +2023-11-09 11:28:03,762:INFO:Set up index. +2023-11-09 11:30:48,846:INFO:PyCaret RegressionExperiment +2023-11-09 11:30:48,846:INFO:Logging name: reg-default-name +2023-11-09 11:30:48,846:INFO:ML Usecase: MLUsecase.REGRESSION +2023-11-09 11:30:48,847:INFO:version 3.1.0 +2023-11-09 11:30:48,847:INFO:Initializing setup() +2023-11-09 11:30:48,847:INFO:self.USI: a07f +2023-11-09 11:30:48,847:INFO:self._variable_keys: {'seed', 'idx', 'transform_target_param', 'gpu_param', 'target_param', 'log_plots_param', 'pipeline', 'logging_param', 'fold_groups_param', '_ml_usecase', 'html_param', 'gpu_n_jobs_param', 'y', 'y_test', 'y_train', 'memory', 'exp_id', 'X_test', 'exp_name_log', 'USI', 'data', 'X_train', 'fold_shuffle_param', 'X', 'fold_generator', 'n_jobs_param', '_available_plots'} +2023-11-09 11:30:48,847:INFO:Checking environment +2023-11-09 11:30:48,847:INFO:python_version: 3.8.18 +2023-11-09 11:30:48,848:INFO:python_build: ('default', 'Sep 11 2023 13:40:15') +2023-11-09 11:30:48,848:INFO:machine: x86_64 +2023-11-09 11:30:48,848:INFO:platform: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:30:48,848:INFO:Memory: svmem(total=8315187200, available=4592553984, percent=44.8, used=3387990016, free=226299904, active=1477255168, inactive=5742903296, buffers=340717568, cached=4360179712, shared=4485120, slab=651247616) +2023-11-09 11:30:48,848:INFO:Physical Core: 1 +2023-11-09 11:30:48,848:INFO:Logical Core: 2 +2023-11-09 11:30:48,849:INFO:Checking libraries +2023-11-09 11:30:48,849:INFO:System: +2023-11-09 11:30:48,849:INFO: python: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] +2023-11-09 11:30:48,849:INFO:executable: /workspaces/D2I-Jupyter-Notebook-Tools/.conda/bin/python +2023-11-09 11:30:48,849:INFO: machine: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:30:48,849:INFO:PyCaret required dependencies: +2023-11-09 11:30:48,849:INFO: pip: 23.3 +2023-11-09 11:30:48,849:INFO: setuptools: 68.0.0 +2023-11-09 11:30:48,849:INFO: pycaret: 3.1.0 +2023-11-09 11:30:48,849:INFO: IPython: 8.12.0 +2023-11-09 11:30:48,849:INFO: ipywidgets: 8.1.1 +2023-11-09 11:30:48,849:INFO: tqdm: 4.66.1 +2023-11-09 11:30:48,849:INFO: numpy: 1.23.5 +2023-11-09 11:30:48,849:INFO: pandas: 1.5.3 +2023-11-09 11:30:48,849:INFO: jinja2: 3.1.2 +2023-11-09 11:30:48,850:INFO: scipy: 1.10.1 +2023-11-09 11:30:48,850:INFO: joblib: 1.3.2 +2023-11-09 11:30:48,850:INFO: sklearn: 1.2.2 +2023-11-09 11:30:48,850:INFO: pyod: 1.1.1 +2023-11-09 11:30:48,850:INFO: imblearn: 0.11.0 +2023-11-09 11:30:48,850:INFO: category_encoders: 2.6.3 +2023-11-09 11:30:48,850:INFO: lightgbm: 4.1.0 +2023-11-09 11:30:48,850:INFO: numba: 0.58.1 +2023-11-09 11:30:48,850:INFO: requests: 2.31.0 +2023-11-09 11:30:48,850:INFO: matplotlib: 3.7.3 +2023-11-09 11:30:48,850:INFO: scikitplot: 0.3.7 +2023-11-09 11:30:48,850:INFO: yellowbrick: 1.5 +2023-11-09 11:30:48,850:INFO: plotly: 5.18.0 +2023-11-09 11:30:48,850:INFO: plotly-resampler: Not installed +2023-11-09 11:30:48,850:INFO: kaleido: 0.2.1 +2023-11-09 11:30:48,850:INFO: schemdraw: 0.15 +2023-11-09 11:30:48,850:INFO: statsmodels: 0.14.0 +2023-11-09 11:30:48,851:INFO: sktime: 0.21.1 +2023-11-09 11:30:48,851:INFO: tbats: 1.1.3 +2023-11-09 11:30:48,851:INFO: pmdarima: 2.0.4 +2023-11-09 11:30:48,851:INFO: psutil: 5.9.0 +2023-11-09 11:30:48,851:INFO: markupsafe: 2.1.3 +2023-11-09 11:30:48,851:INFO: pickle5: Not installed +2023-11-09 11:30:48,851:INFO: cloudpickle: 3.0.0 +2023-11-09 11:30:48,851:INFO: deprecation: 2.1.0 +2023-11-09 11:30:48,851:INFO: xxhash: 3.4.1 +2023-11-09 11:30:48,851:INFO: wurlitzer: 3.0.3 +2023-11-09 11:30:48,851:INFO:PyCaret optional dependencies: +2023-11-09 11:30:48,851:INFO: shap: Not installed +2023-11-09 11:30:48,851:INFO: interpret: Not installed +2023-11-09 11:30:48,851:INFO: umap: Not installed +2023-11-09 11:30:48,851:INFO: ydata_profiling: Not installed +2023-11-09 11:30:48,851:INFO: explainerdashboard: Not installed +2023-11-09 11:30:48,851:INFO: autoviz: Not installed +2023-11-09 11:30:48,851:INFO: fairlearn: Not installed +2023-11-09 11:30:48,852:INFO: deepchecks: Not installed +2023-11-09 11:30:48,852:INFO: xgboost: Not installed +2023-11-09 11:30:48,852:INFO: catboost: Not installed +2023-11-09 11:30:48,852:INFO: kmodes: Not installed +2023-11-09 11:30:48,852:INFO: mlxtend: Not installed +2023-11-09 11:30:48,852:INFO: statsforecast: Not installed +2023-11-09 11:30:48,852:INFO: tune_sklearn: Not installed +2023-11-09 11:30:48,852:INFO: ray: Not installed +2023-11-09 11:30:48,852:INFO: hyperopt: Not installed +2023-11-09 11:30:48,852:INFO: optuna: Not installed +2023-11-09 11:30:48,852:INFO: skopt: Not installed +2023-11-09 11:30:48,852:INFO: mlflow: Not installed +2023-11-09 11:30:48,852:INFO: gradio: Not installed +2023-11-09 11:30:48,852:INFO: fastapi: Not installed +2023-11-09 11:30:48,852:INFO: uvicorn: Not installed +2023-11-09 11:30:48,852:INFO: m2cgen: Not installed +2023-11-09 11:30:48,852:INFO: evidently: Not installed +2023-11-09 11:30:48,852:INFO: fugue: Not installed +2023-11-09 11:30:48,852:INFO: streamlit: Not installed +2023-11-09 11:30:48,852:INFO: prophet: Not installed +2023-11-09 11:30:48,853:INFO:None +2023-11-09 11:30:48,853:INFO:Set up data. +2023-11-09 11:30:48,856:INFO:Set up folding strategy. +2023-11-09 11:30:48,856:INFO:Set up train/test split. +2023-11-09 11:30:48,856:INFO:Set up data. +2023-11-09 11:30:48,860:INFO:Set up index. +2023-11-09 11:30:48,860:INFO:Assigning column types. +2023-11-09 11:30:48,864:INFO:Engine successfully changes for model 'lr' to 'sklearn'. +2023-11-09 11:30:48,864:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:30:48,868:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:30:48,872:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:30:48,927:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:30:48,986:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:30:48,988:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:48,988:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:48,989:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:30:48,996:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,003:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,059:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,097:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,097:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,097:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,098:INFO:Engine successfully changes for model 'lasso' to 'sklearn'. +2023-11-09 11:30:49,102:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,105:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,154:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,192:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,192:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,192:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,196:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,200:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,248:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,284:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,284:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,284:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,285:INFO:Engine successfully changes for model 'ridge' to 'sklearn'. +2023-11-09 11:30:49,292:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,340:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,376:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,377:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,377:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,385:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,432:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,468:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,469:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,469:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,470:INFO:Engine successfully changes for model 'en' to 'sklearn'. +2023-11-09 11:30:49,525:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,567:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,568:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,568:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,627:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,663:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,664:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,664:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,664:INFO:Engine successfully changes for model 'knn' to 'sklearn'. +2023-11-09 11:30:49,723:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,763:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,764:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,820:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:30:49,857:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,858:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,858:INFO:Engine successfully changes for model 'svm' to 'sklearn'. +2023-11-09 11:30:49,952:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:49,952:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:50,064:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:50,064:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:50,065:INFO:Preparing preprocessing pipeline... +2023-11-09 11:30:50,065:INFO:Set up target transformation. +2023-11-09 11:30:50,065:INFO:Set up simple imputation. +2023-11-09 11:30:50,066:INFO:Set up column name cleaning. +2023-11-09 11:30:50,090:INFO:Finished creating preprocessing pipeline. +2023-11-09 11:30:50,096:INFO:Pipeline: Pipeline(memory=FastMemory(location=/tmp/joblib), + steps=[('target_transformation', + TransformerWrapperWithInverse(transformer=TargetTransformer(estimator=PowerTransformer(standardize=False)))), + ('numerical_imputer', + TransformerWrapper(include=['Year'], + transformer=SimpleImputer())), + ('categorical_imputer', + TransformerWrapper(include=[], + transformer=SimpleImputer(strategy='most_frequent'))), + ('clean_column_names', + TransformerWrapper(transformer=CleanColumnNames()))]) +2023-11-09 11:30:50,096:INFO:Creating final display dataframe. +2023-11-09 11:30:50,166:INFO:Setup _display_container: Description Value +0 Session id 123 +1 Target Average price All property types +2 Target type Regression +3 Original data shape (523, 4) +4 Transformed data shape (523, 4) +5 Transformed train set shape (372, 4) +6 Transformed test set shape (151, 4) +7 Numeric features 1 +8 Preprocess True +9 Imputation type simple +10 Numeric imputation mean +11 Categorical imputation mode +12 Transform target True +13 Transform target method yeo-johnson +14 Fold Generator TimeSeriesSplit +15 Fold Number 3 +16 CPU Jobs -1 +17 Use GPU False +18 Log Experiment False +19 Experiment Name reg-default-name +20 USI a07f +2023-11-09 11:30:50,297:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:50,298:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:50,417:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:50,417:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:30:50,418:INFO:setup() successfully completed in 1.57s............... +2023-11-09 11:30:50,490:INFO:Initializing compare_models() +2023-11-09 11:30:50,491:INFO:compare_models(self=, include=None, fold=None, round=4, cross_validation=True, sort=MAE, n_select=1, budget_time=None, turbo=True, errors=ignore, fit_kwargs=None, groups=None, experiment_custom_tags=None, probability_threshold=None, verbose=True, parallel=None, caller_params={'self': , 'include': None, 'exclude': None, 'fold': None, 'round': 4, 'cross_validation': True, 'sort': 'MAE', 'n_select': 1, 'budget_time': None, 'turbo': True, 'errors': 'ignore', 'fit_kwargs': None, 'groups': None, 'experiment_custom_tags': None, 'engine': None, 'verbose': True, 'parallel': None, '__class__': }, exclude=None) +2023-11-09 11:30:50,491:INFO:Checking exceptions +2023-11-09 11:30:50,493:INFO:Preparing display monitor +2023-11-09 11:30:50,516:INFO:Initializing Linear Regression +2023-11-09 11:30:50,517:INFO:Total runtime is 6.373723347981771e-06 minutes +2023-11-09 11:30:50,519:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:50,520:INFO:Initializing create_model() +2023-11-09 11:30:50,520:INFO:create_model(self=, estimator=lr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:50,520:INFO:Checking exceptions +2023-11-09 11:30:50,520:INFO:Importing libraries +2023-11-09 11:30:50,520:INFO:Copying training dataset +2023-11-09 11:30:50,523:INFO:Defining folds +2023-11-09 11:30:50,524:INFO:Declaring metric variables +2023-11-09 11:30:50,527:INFO:Importing untrained model +2023-11-09 11:30:50,530:INFO:Linear Regression Imported successfully +2023-11-09 11:30:50,536:INFO:Starting cross validation +2023-11-09 11:30:50,538:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:50,683:INFO:Calculating mean and std +2023-11-09 11:30:50,683:INFO:Creating metrics dataframe +2023-11-09 11:30:50,687:INFO:Uploading results into container +2023-11-09 11:30:50,688:INFO:Uploading model into container now +2023-11-09 11:30:50,689:INFO:_master_model_container: 1 +2023-11-09 11:30:50,689:INFO:_display_container: 2 +2023-11-09 11:30:50,689:INFO:LinearRegression(n_jobs=-1) +2023-11-09 11:30:50,689:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:50,819:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:50,819:INFO:Creating metrics dataframe +2023-11-09 11:30:50,827:INFO:Initializing Lasso Regression +2023-11-09 11:30:50,827:INFO:Total runtime is 0.005178121725718181 minutes +2023-11-09 11:30:50,830:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:50,831:INFO:Initializing create_model() +2023-11-09 11:30:50,831:INFO:create_model(self=, estimator=lasso, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:50,831:INFO:Checking exceptions +2023-11-09 11:30:50,831:INFO:Importing libraries +2023-11-09 11:30:50,831:INFO:Copying training dataset +2023-11-09 11:30:50,834:INFO:Defining folds +2023-11-09 11:30:50,834:INFO:Declaring metric variables +2023-11-09 11:30:50,837:INFO:Importing untrained model +2023-11-09 11:30:50,840:INFO:Lasso Regression Imported successfully +2023-11-09 11:30:50,846:INFO:Starting cross validation +2023-11-09 11:30:50,847:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:50,955:INFO:Calculating mean and std +2023-11-09 11:30:50,956:INFO:Creating metrics dataframe +2023-11-09 11:30:50,959:INFO:Uploading results into container +2023-11-09 11:30:50,959:INFO:Uploading model into container now +2023-11-09 11:30:50,959:INFO:_master_model_container: 2 +2023-11-09 11:30:50,959:INFO:_display_container: 2 +2023-11-09 11:30:50,960:INFO:Lasso(random_state=123) +2023-11-09 11:30:50,960:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:51,091:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:51,092:INFO:Creating metrics dataframe +2023-11-09 11:30:51,105:INFO:Initializing Ridge Regression +2023-11-09 11:30:51,105:INFO:Total runtime is 0.009818077087402344 minutes +2023-11-09 11:30:51,113:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:51,114:INFO:Initializing create_model() +2023-11-09 11:30:51,114:INFO:create_model(self=, estimator=ridge, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:51,114:INFO:Checking exceptions +2023-11-09 11:30:51,114:INFO:Importing libraries +2023-11-09 11:30:51,114:INFO:Copying training dataset +2023-11-09 11:30:51,118:INFO:Defining folds +2023-11-09 11:30:51,118:INFO:Declaring metric variables +2023-11-09 11:30:51,122:INFO:Importing untrained model +2023-11-09 11:30:51,125:INFO:Ridge Regression Imported successfully +2023-11-09 11:30:51,131:INFO:Starting cross validation +2023-11-09 11:30:51,132:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:51,204:INFO:Calculating mean and std +2023-11-09 11:30:51,205:INFO:Creating metrics dataframe +2023-11-09 11:30:51,208:INFO:Uploading results into container +2023-11-09 11:30:51,208:INFO:Uploading model into container now +2023-11-09 11:30:51,209:INFO:_master_model_container: 3 +2023-11-09 11:30:51,209:INFO:_display_container: 2 +2023-11-09 11:30:51,209:INFO:Ridge(random_state=123) +2023-11-09 11:30:51,209:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:51,333:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:51,333:INFO:Creating metrics dataframe +2023-11-09 11:30:51,342:INFO:Initializing Elastic Net +2023-11-09 11:30:51,342:INFO:Total runtime is 0.013759422302246093 minutes +2023-11-09 11:30:51,345:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:51,346:INFO:Initializing create_model() +2023-11-09 11:30:51,346:INFO:create_model(self=, estimator=en, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:51,346:INFO:Checking exceptions +2023-11-09 11:30:51,346:INFO:Importing libraries +2023-11-09 11:30:51,346:INFO:Copying training dataset +2023-11-09 11:30:51,348:INFO:Defining folds +2023-11-09 11:30:51,349:INFO:Declaring metric variables +2023-11-09 11:30:51,351:INFO:Importing untrained model +2023-11-09 11:30:51,354:INFO:Elastic Net Imported successfully +2023-11-09 11:30:51,360:INFO:Starting cross validation +2023-11-09 11:30:51,361:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:51,434:INFO:Calculating mean and std +2023-11-09 11:30:51,435:INFO:Creating metrics dataframe +2023-11-09 11:30:51,437:INFO:Uploading results into container +2023-11-09 11:30:51,438:INFO:Uploading model into container now +2023-11-09 11:30:51,438:INFO:_master_model_container: 4 +2023-11-09 11:30:51,438:INFO:_display_container: 2 +2023-11-09 11:30:51,439:INFO:ElasticNet(random_state=123) +2023-11-09 11:30:51,439:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:51,566:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:51,566:INFO:Creating metrics dataframe +2023-11-09 11:30:51,575:INFO:Initializing Least Angle Regression +2023-11-09 11:30:51,575:INFO:Total runtime is 0.017643757661183673 minutes +2023-11-09 11:30:51,578:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:51,579:INFO:Initializing create_model() +2023-11-09 11:30:51,579:INFO:create_model(self=, estimator=lar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:51,579:INFO:Checking exceptions +2023-11-09 11:30:51,579:INFO:Importing libraries +2023-11-09 11:30:51,579:INFO:Copying training dataset +2023-11-09 11:30:51,582:INFO:Defining folds +2023-11-09 11:30:51,583:INFO:Declaring metric variables +2023-11-09 11:30:51,586:INFO:Importing untrained model +2023-11-09 11:30:51,589:INFO:Least Angle Regression Imported successfully +2023-11-09 11:30:51,595:INFO:Starting cross validation +2023-11-09 11:30:51,596:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:51,683:INFO:Calculating mean and std +2023-11-09 11:30:51,684:INFO:Creating metrics dataframe +2023-11-09 11:30:51,688:INFO:Uploading results into container +2023-11-09 11:30:51,689:INFO:Uploading model into container now +2023-11-09 11:30:51,689:INFO:_master_model_container: 5 +2023-11-09 11:30:51,689:INFO:_display_container: 2 +2023-11-09 11:30:51,689:INFO:Lars(random_state=123) +2023-11-09 11:30:51,689:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:51,818:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:51,818:INFO:Creating metrics dataframe +2023-11-09 11:30:51,827:INFO:Initializing Lasso Least Angle Regression +2023-11-09 11:30:51,827:INFO:Total runtime is 0.021846044063568115 minutes +2023-11-09 11:30:51,830:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:51,831:INFO:Initializing create_model() +2023-11-09 11:30:51,831:INFO:create_model(self=, estimator=llar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:51,831:INFO:Checking exceptions +2023-11-09 11:30:51,831:INFO:Importing libraries +2023-11-09 11:30:51,831:INFO:Copying training dataset +2023-11-09 11:30:51,834:INFO:Defining folds +2023-11-09 11:30:51,835:INFO:Declaring metric variables +2023-11-09 11:30:51,838:INFO:Importing untrained model +2023-11-09 11:30:51,841:INFO:Lasso Least Angle Regression Imported successfully +2023-11-09 11:30:51,847:INFO:Starting cross validation +2023-11-09 11:30:51,848:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:51,927:INFO:Calculating mean and std +2023-11-09 11:30:51,928:INFO:Creating metrics dataframe +2023-11-09 11:30:51,930:INFO:Uploading results into container +2023-11-09 11:30:51,931:INFO:Uploading model into container now +2023-11-09 11:30:51,931:INFO:_master_model_container: 6 +2023-11-09 11:30:51,931:INFO:_display_container: 2 +2023-11-09 11:30:51,931:INFO:LassoLars(random_state=123) +2023-11-09 11:30:51,931:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:52,058:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:52,058:INFO:Creating metrics dataframe +2023-11-09 11:30:52,068:INFO:Initializing Orthogonal Matching Pursuit +2023-11-09 11:30:52,068:INFO:Total runtime is 0.025870112578074138 minutes +2023-11-09 11:30:52,072:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:52,072:INFO:Initializing create_model() +2023-11-09 11:30:52,073:INFO:create_model(self=, estimator=omp, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:52,073:INFO:Checking exceptions +2023-11-09 11:30:52,073:INFO:Importing libraries +2023-11-09 11:30:52,073:INFO:Copying training dataset +2023-11-09 11:30:52,076:INFO:Defining folds +2023-11-09 11:30:52,076:INFO:Declaring metric variables +2023-11-09 11:30:52,079:INFO:Importing untrained model +2023-11-09 11:30:52,083:INFO:Orthogonal Matching Pursuit Imported successfully +2023-11-09 11:30:52,088:INFO:Starting cross validation +2023-11-09 11:30:52,089:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:52,167:INFO:Calculating mean and std +2023-11-09 11:30:52,168:INFO:Creating metrics dataframe +2023-11-09 11:30:52,171:INFO:Uploading results into container +2023-11-09 11:30:52,171:INFO:Uploading model into container now +2023-11-09 11:30:52,171:INFO:_master_model_container: 7 +2023-11-09 11:30:52,171:INFO:_display_container: 2 +2023-11-09 11:30:52,172:INFO:OrthogonalMatchingPursuit() +2023-11-09 11:30:52,172:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:52,302:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:52,302:INFO:Creating metrics dataframe +2023-11-09 11:30:52,311:INFO:Initializing Bayesian Ridge +2023-11-09 11:30:52,311:INFO:Total runtime is 0.029915579160054526 minutes +2023-11-09 11:30:52,314:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:52,315:INFO:Initializing create_model() +2023-11-09 11:30:52,315:INFO:create_model(self=, estimator=br, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:52,315:INFO:Checking exceptions +2023-11-09 11:30:52,315:INFO:Importing libraries +2023-11-09 11:30:52,316:INFO:Copying training dataset +2023-11-09 11:30:52,319:INFO:Defining folds +2023-11-09 11:30:52,320:INFO:Declaring metric variables +2023-11-09 11:30:52,323:INFO:Importing untrained model +2023-11-09 11:30:52,326:INFO:Bayesian Ridge Imported successfully +2023-11-09 11:30:52,332:INFO:Starting cross validation +2023-11-09 11:30:52,333:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:52,408:INFO:Calculating mean and std +2023-11-09 11:30:52,409:INFO:Creating metrics dataframe +2023-11-09 11:30:52,413:INFO:Uploading results into container +2023-11-09 11:30:52,413:INFO:Uploading model into container now +2023-11-09 11:30:52,413:INFO:_master_model_container: 8 +2023-11-09 11:30:52,413:INFO:_display_container: 2 +2023-11-09 11:30:52,414:INFO:BayesianRidge() +2023-11-09 11:30:52,414:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:52,534:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:52,534:INFO:Creating metrics dataframe +2023-11-09 11:30:52,547:INFO:Initializing Passive Aggressive Regressor +2023-11-09 11:30:52,547:INFO:Total runtime is 0.03383957544962565 minutes +2023-11-09 11:30:52,554:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:52,555:INFO:Initializing create_model() +2023-11-09 11:30:52,555:INFO:create_model(self=, estimator=par, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:52,555:INFO:Checking exceptions +2023-11-09 11:30:52,555:INFO:Importing libraries +2023-11-09 11:30:52,555:INFO:Copying training dataset +2023-11-09 11:30:52,562:INFO:Defining folds +2023-11-09 11:30:52,562:INFO:Declaring metric variables +2023-11-09 11:30:52,565:INFO:Importing untrained model +2023-11-09 11:30:52,568:INFO:Passive Aggressive Regressor Imported successfully +2023-11-09 11:30:52,574:INFO:Starting cross validation +2023-11-09 11:30:52,575:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:52,652:INFO:Calculating mean and std +2023-11-09 11:30:52,653:INFO:Creating metrics dataframe +2023-11-09 11:30:52,656:INFO:Uploading results into container +2023-11-09 11:30:52,657:INFO:Uploading model into container now +2023-11-09 11:30:52,657:INFO:_master_model_container: 9 +2023-11-09 11:30:52,657:INFO:_display_container: 2 +2023-11-09 11:30:52,657:INFO:PassiveAggressiveRegressor(random_state=123) +2023-11-09 11:30:52,658:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:52,799:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:52,799:INFO:Creating metrics dataframe +2023-11-09 11:30:52,812:INFO:Initializing Huber Regressor +2023-11-09 11:30:52,812:INFO:Total runtime is 0.0382700244585673 minutes +2023-11-09 11:30:52,816:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:52,816:INFO:Initializing create_model() +2023-11-09 11:30:52,816:INFO:create_model(self=, estimator=huber, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:52,817:INFO:Checking exceptions +2023-11-09 11:30:52,817:INFO:Importing libraries +2023-11-09 11:30:52,817:INFO:Copying training dataset +2023-11-09 11:30:52,821:INFO:Defining folds +2023-11-09 11:30:52,821:INFO:Declaring metric variables +2023-11-09 11:30:52,825:INFO:Importing untrained model +2023-11-09 11:30:52,828:INFO:Huber Regressor Imported successfully +2023-11-09 11:30:52,835:INFO:Starting cross validation +2023-11-09 11:30:52,836:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:52,954:INFO:Calculating mean and std +2023-11-09 11:30:52,955:INFO:Creating metrics dataframe +2023-11-09 11:30:52,959:INFO:Uploading results into container +2023-11-09 11:30:52,960:INFO:Uploading model into container now +2023-11-09 11:30:52,960:INFO:_master_model_container: 10 +2023-11-09 11:30:52,960:INFO:_display_container: 2 +2023-11-09 11:30:52,960:INFO:HuberRegressor() +2023-11-09 11:30:52,960:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:53,091:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:53,091:INFO:Creating metrics dataframe +2023-11-09 11:30:53,101:INFO:Initializing K Neighbors Regressor +2023-11-09 11:30:53,101:INFO:Total runtime is 0.04307561715443929 minutes +2023-11-09 11:30:53,104:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:53,105:INFO:Initializing create_model() +2023-11-09 11:30:53,105:INFO:create_model(self=, estimator=knn, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:53,105:INFO:Checking exceptions +2023-11-09 11:30:53,105:INFO:Importing libraries +2023-11-09 11:30:53,105:INFO:Copying training dataset +2023-11-09 11:30:53,108:INFO:Defining folds +2023-11-09 11:30:53,109:INFO:Declaring metric variables +2023-11-09 11:30:53,112:INFO:Importing untrained model +2023-11-09 11:30:53,115:INFO:K Neighbors Regressor Imported successfully +2023-11-09 11:30:53,121:INFO:Starting cross validation +2023-11-09 11:30:53,122:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:53,267:INFO:Calculating mean and std +2023-11-09 11:30:53,268:INFO:Creating metrics dataframe +2023-11-09 11:30:53,272:INFO:Uploading results into container +2023-11-09 11:30:53,272:INFO:Uploading model into container now +2023-11-09 11:30:53,273:INFO:_master_model_container: 11 +2023-11-09 11:30:53,273:INFO:_display_container: 2 +2023-11-09 11:30:53,273:INFO:KNeighborsRegressor(n_jobs=-1) +2023-11-09 11:30:53,273:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:53,396:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:53,396:INFO:Creating metrics dataframe +2023-11-09 11:30:53,407:INFO:Initializing Decision Tree Regressor +2023-11-09 11:30:53,408:INFO:Total runtime is 0.048187617460886636 minutes +2023-11-09 11:30:53,411:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:53,411:INFO:Initializing create_model() +2023-11-09 11:30:53,411:INFO:create_model(self=, estimator=dt, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:53,411:INFO:Checking exceptions +2023-11-09 11:30:53,411:INFO:Importing libraries +2023-11-09 11:30:53,411:INFO:Copying training dataset +2023-11-09 11:30:53,415:INFO:Defining folds +2023-11-09 11:30:53,416:INFO:Declaring metric variables +2023-11-09 11:30:53,419:INFO:Importing untrained model +2023-11-09 11:30:53,423:INFO:Decision Tree Regressor Imported successfully +2023-11-09 11:30:53,428:INFO:Starting cross validation +2023-11-09 11:30:53,429:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:53,501:INFO:Calculating mean and std +2023-11-09 11:30:53,501:INFO:Creating metrics dataframe +2023-11-09 11:30:53,504:INFO:Uploading results into container +2023-11-09 11:30:53,505:INFO:Uploading model into container now +2023-11-09 11:30:53,505:INFO:_master_model_container: 12 +2023-11-09 11:30:53,505:INFO:_display_container: 2 +2023-11-09 11:30:53,505:INFO:DecisionTreeRegressor(random_state=123) +2023-11-09 11:30:53,506:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:53,629:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:53,629:INFO:Creating metrics dataframe +2023-11-09 11:30:53,640:INFO:Initializing Random Forest Regressor +2023-11-09 11:30:53,640:INFO:Total runtime is 0.0520611564318339 minutes +2023-11-09 11:30:53,644:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:53,644:INFO:Initializing create_model() +2023-11-09 11:30:53,645:INFO:create_model(self=, estimator=rf, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:53,645:INFO:Checking exceptions +2023-11-09 11:30:53,645:INFO:Importing libraries +2023-11-09 11:30:53,645:INFO:Copying training dataset +2023-11-09 11:30:53,648:INFO:Defining folds +2023-11-09 11:30:53,648:INFO:Declaring metric variables +2023-11-09 11:30:53,652:INFO:Importing untrained model +2023-11-09 11:30:53,657:INFO:Random Forest Regressor Imported successfully +2023-11-09 11:30:53,663:INFO:Starting cross validation +2023-11-09 11:30:53,664:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:54,056:INFO:Calculating mean and std +2023-11-09 11:30:54,058:INFO:Creating metrics dataframe +2023-11-09 11:30:54,064:INFO:Uploading results into container +2023-11-09 11:30:54,064:INFO:Uploading model into container now +2023-11-09 11:30:54,064:INFO:_master_model_container: 13 +2023-11-09 11:30:54,064:INFO:_display_container: 2 +2023-11-09 11:30:54,065:INFO:RandomForestRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:30:54,065:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:54,191:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:54,192:INFO:Creating metrics dataframe +2023-11-09 11:30:54,202:INFO:Initializing Extra Trees Regressor +2023-11-09 11:30:54,202:INFO:Total runtime is 0.06143279075622558 minutes +2023-11-09 11:30:54,206:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:54,206:INFO:Initializing create_model() +2023-11-09 11:30:54,206:INFO:create_model(self=, estimator=et, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:54,206:INFO:Checking exceptions +2023-11-09 11:30:54,206:INFO:Importing libraries +2023-11-09 11:30:54,206:INFO:Copying training dataset +2023-11-09 11:30:54,210:INFO:Defining folds +2023-11-09 11:30:54,210:INFO:Declaring metric variables +2023-11-09 11:30:54,213:INFO:Importing untrained model +2023-11-09 11:30:54,217:INFO:Extra Trees Regressor Imported successfully +2023-11-09 11:30:54,223:INFO:Starting cross validation +2023-11-09 11:30:54,224:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:54,553:INFO:Calculating mean and std +2023-11-09 11:30:54,555:INFO:Creating metrics dataframe +2023-11-09 11:30:54,558:INFO:Uploading results into container +2023-11-09 11:30:54,559:INFO:Uploading model into container now +2023-11-09 11:30:54,559:INFO:_master_model_container: 14 +2023-11-09 11:30:54,559:INFO:_display_container: 2 +2023-11-09 11:30:54,560:INFO:ExtraTreesRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:30:54,560:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:54,698:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:54,698:INFO:Creating metrics dataframe +2023-11-09 11:30:54,711:INFO:Initializing AdaBoost Regressor +2023-11-09 11:30:54,711:INFO:Total runtime is 0.06991639931996663 minutes +2023-11-09 11:30:54,715:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:54,716:INFO:Initializing create_model() +2023-11-09 11:30:54,716:INFO:create_model(self=, estimator=ada, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:54,716:INFO:Checking exceptions +2023-11-09 11:30:54,716:INFO:Importing libraries +2023-11-09 11:30:54,716:INFO:Copying training dataset +2023-11-09 11:30:54,719:INFO:Defining folds +2023-11-09 11:30:54,720:INFO:Declaring metric variables +2023-11-09 11:30:54,723:INFO:Importing untrained model +2023-11-09 11:30:54,726:INFO:AdaBoost Regressor Imported successfully +2023-11-09 11:30:54,732:INFO:Starting cross validation +2023-11-09 11:30:54,733:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:55,167:INFO:Calculating mean and std +2023-11-09 11:30:55,168:INFO:Creating metrics dataframe +2023-11-09 11:30:55,173:INFO:Uploading results into container +2023-11-09 11:30:55,174:INFO:Uploading model into container now +2023-11-09 11:30:55,174:INFO:_master_model_container: 15 +2023-11-09 11:30:55,174:INFO:_display_container: 2 +2023-11-09 11:30:55,174:INFO:AdaBoostRegressor(random_state=123) +2023-11-09 11:30:55,175:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:55,322:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:55,323:INFO:Creating metrics dataframe +2023-11-09 11:30:55,333:INFO:Initializing Gradient Boosting Regressor +2023-11-09 11:30:55,333:INFO:Total runtime is 0.08028226693471271 minutes +2023-11-09 11:30:55,337:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:55,337:INFO:Initializing create_model() +2023-11-09 11:30:55,337:INFO:create_model(self=, estimator=gbr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:55,337:INFO:Checking exceptions +2023-11-09 11:30:55,337:INFO:Importing libraries +2023-11-09 11:30:55,337:INFO:Copying training dataset +2023-11-09 11:30:55,341:INFO:Defining folds +2023-11-09 11:30:55,341:INFO:Declaring metric variables +2023-11-09 11:30:55,345:INFO:Importing untrained model +2023-11-09 11:30:55,348:INFO:Gradient Boosting Regressor Imported successfully +2023-11-09 11:30:55,354:INFO:Starting cross validation +2023-11-09 11:30:55,355:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:55,608:INFO:Calculating mean and std +2023-11-09 11:30:55,609:INFO:Creating metrics dataframe +2023-11-09 11:30:55,613:INFO:Uploading results into container +2023-11-09 11:30:55,614:INFO:Uploading model into container now +2023-11-09 11:30:55,614:INFO:_master_model_container: 16 +2023-11-09 11:30:55,614:INFO:_display_container: 2 +2023-11-09 11:30:55,614:INFO:GradientBoostingRegressor(random_state=123) +2023-11-09 11:30:55,614:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:55,759:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:55,760:INFO:Creating metrics dataframe +2023-11-09 11:30:55,772:INFO:Initializing Light Gradient Boosting Machine +2023-11-09 11:30:55,772:INFO:Total runtime is 0.0875914971033732 minutes +2023-11-09 11:30:55,776:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:55,776:INFO:Initializing create_model() +2023-11-09 11:30:55,776:INFO:create_model(self=, estimator=lightgbm, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:55,776:INFO:Checking exceptions +2023-11-09 11:30:55,777:INFO:Importing libraries +2023-11-09 11:30:55,777:INFO:Copying training dataset +2023-11-09 11:30:55,780:INFO:Defining folds +2023-11-09 11:30:55,781:INFO:Declaring metric variables +2023-11-09 11:30:55,784:INFO:Importing untrained model +2023-11-09 11:30:55,788:INFO:Light Gradient Boosting Machine Imported successfully +2023-11-09 11:30:55,795:INFO:Starting cross validation +2023-11-09 11:30:55,796:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:56,276:INFO:Calculating mean and std +2023-11-09 11:30:56,277:INFO:Creating metrics dataframe +2023-11-09 11:30:56,280:INFO:Uploading results into container +2023-11-09 11:30:56,281:INFO:Uploading model into container now +2023-11-09 11:30:56,282:INFO:_master_model_container: 17 +2023-11-09 11:30:56,282:INFO:_display_container: 2 +2023-11-09 11:30:56,282:INFO:LGBMRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:30:56,282:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:56,420:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:56,421:INFO:Creating metrics dataframe +2023-11-09 11:30:56,432:INFO:Initializing Dummy Regressor +2023-11-09 11:30:56,433:INFO:Total runtime is 0.09860765933990479 minutes +2023-11-09 11:30:56,436:INFO:SubProcess create_model() called ================================== +2023-11-09 11:30:56,437:INFO:Initializing create_model() +2023-11-09 11:30:56,437:INFO:create_model(self=, estimator=dummy, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:56,437:INFO:Checking exceptions +2023-11-09 11:30:56,437:INFO:Importing libraries +2023-11-09 11:30:56,437:INFO:Copying training dataset +2023-11-09 11:30:56,440:INFO:Defining folds +2023-11-09 11:30:56,441:INFO:Declaring metric variables +2023-11-09 11:30:56,444:INFO:Importing untrained model +2023-11-09 11:30:56,447:INFO:Dummy Regressor Imported successfully +2023-11-09 11:30:56,454:INFO:Starting cross validation +2023-11-09 11:30:56,455:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:30:56,524:INFO:Calculating mean and std +2023-11-09 11:30:56,525:INFO:Creating metrics dataframe +2023-11-09 11:30:56,529:INFO:Uploading results into container +2023-11-09 11:30:56,529:INFO:Uploading model into container now +2023-11-09 11:30:56,530:INFO:_master_model_container: 18 +2023-11-09 11:30:56,530:INFO:_display_container: 2 +2023-11-09 11:30:56,530:INFO:DummyRegressor() +2023-11-09 11:30:56,530:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:56,654:INFO:SubProcess create_model() end ================================== +2023-11-09 11:30:56,654:INFO:Creating metrics dataframe +2023-11-09 11:30:56,676:INFO:Initializing create_model() +2023-11-09 11:30:56,676:INFO:create_model(self=, estimator=HuberRegressor(), fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=False, predict=False, fit_kwargs={}, groups=None, refit=True, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=None, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:30:56,676:INFO:Checking exceptions +2023-11-09 11:30:56,678:INFO:Importing libraries +2023-11-09 11:30:56,678:INFO:Copying training dataset +2023-11-09 11:30:56,680:INFO:Defining folds +2023-11-09 11:30:56,680:INFO:Declaring metric variables +2023-11-09 11:30:56,681:INFO:Importing untrained model +2023-11-09 11:30:56,681:INFO:Declaring custom model +2023-11-09 11:30:56,681:INFO:Huber Regressor Imported successfully +2023-11-09 11:30:56,682:INFO:Cross validation set to False +2023-11-09 11:30:56,682:INFO:Fitting Model +2023-11-09 11:30:56,706:INFO:HuberRegressor() +2023-11-09 11:30:56,707:INFO:create_model() successfully completed...................................... +2023-11-09 11:30:56,862:INFO:_master_model_container: 18 +2023-11-09 11:30:56,863:INFO:_display_container: 2 +2023-11-09 11:30:56,863:INFO:HuberRegressor() +2023-11-09 11:30:56,863:INFO:compare_models() successfully completed...................................... +2023-11-09 11:30:57,345:INFO:Initializing predict_model() +2023-11-09 11:30:57,345:INFO:predict_model(self=, estimator=HuberRegressor(), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=.encode_labels at 0x7fbb2cc9ef70>) +2023-11-09 11:30:57,346:INFO:Checking exceptions +2023-11-09 11:30:57,346:INFO:Preloading libraries +2023-11-09 11:30:57,348:INFO:Set up data. +2023-11-09 11:30:57,351:INFO:Set up index. +2023-11-09 11:32:42,159:INFO:Initializing predict_model() +2023-11-09 11:32:42,160:INFO:predict_model(self=, estimator=HuberRegressor(), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=.encode_labels at 0x7fbb2cdcb790>) +2023-11-09 11:32:42,160:INFO:Checking exceptions +2023-11-09 11:32:42,160:INFO:Preloading libraries +2023-11-09 11:32:42,162:INFO:Set up data. +2023-11-09 11:32:42,165:INFO:Set up index. +2023-11-09 11:35:31,536:INFO:PyCaret RegressionExperiment +2023-11-09 11:35:31,537:INFO:Logging name: reg-default-name +2023-11-09 11:35:31,537:INFO:ML Usecase: MLUsecase.REGRESSION +2023-11-09 11:35:31,537:INFO:version 3.1.0 +2023-11-09 11:35:31,537:INFO:Initializing setup() +2023-11-09 11:35:31,537:INFO:self.USI: c4a4 +2023-11-09 11:35:31,537:INFO:self._variable_keys: {'seed', 'idx', 'transform_target_param', 'gpu_param', 'target_param', 'log_plots_param', 'pipeline', 'logging_param', 'fold_groups_param', '_ml_usecase', 'html_param', 'gpu_n_jobs_param', 'y', 'y_test', 'y_train', 'memory', 'exp_id', 'X_test', 'exp_name_log', 'USI', 'data', 'X_train', 'fold_shuffle_param', 'X', 'fold_generator', 'n_jobs_param', '_available_plots'} +2023-11-09 11:35:31,538:INFO:Checking environment +2023-11-09 11:35:31,538:INFO:python_version: 3.8.18 +2023-11-09 11:35:31,538:INFO:python_build: ('default', 'Sep 11 2023 13:40:15') +2023-11-09 11:35:31,538:INFO:machine: x86_64 +2023-11-09 11:35:31,538:INFO:platform: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:35:31,538:INFO:Memory: svmem(total=8315187200, available=4608188416, percent=44.6, used=3372351488, free=231645184, active=1478742016, inactive=5784244224, buffers=342511616, cached=4368678912, shared=4489216, slab=651292672) +2023-11-09 11:35:31,539:INFO:Physical Core: 1 +2023-11-09 11:35:31,539:INFO:Logical Core: 2 +2023-11-09 11:35:31,539:INFO:Checking libraries +2023-11-09 11:35:31,539:INFO:System: +2023-11-09 11:35:31,539:INFO: python: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] +2023-11-09 11:35:31,539:INFO:executable: /workspaces/D2I-Jupyter-Notebook-Tools/.conda/bin/python +2023-11-09 11:35:31,539:INFO: machine: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:35:31,539:INFO:PyCaret required dependencies: +2023-11-09 11:35:31,539:INFO: pip: 23.3 +2023-11-09 11:35:31,539:INFO: setuptools: 68.0.0 +2023-11-09 11:35:31,539:INFO: pycaret: 3.1.0 +2023-11-09 11:35:31,539:INFO: IPython: 8.12.0 +2023-11-09 11:35:31,539:INFO: ipywidgets: 8.1.1 +2023-11-09 11:35:31,540:INFO: tqdm: 4.66.1 +2023-11-09 11:35:31,540:INFO: numpy: 1.23.5 +2023-11-09 11:35:31,540:INFO: pandas: 1.5.3 +2023-11-09 11:35:31,540:INFO: jinja2: 3.1.2 +2023-11-09 11:35:31,540:INFO: scipy: 1.10.1 +2023-11-09 11:35:31,540:INFO: joblib: 1.3.2 +2023-11-09 11:35:31,540:INFO: sklearn: 1.2.2 +2023-11-09 11:35:31,540:INFO: pyod: 1.1.1 +2023-11-09 11:35:31,540:INFO: imblearn: 0.11.0 +2023-11-09 11:35:31,540:INFO: category_encoders: 2.6.3 +2023-11-09 11:35:31,540:INFO: lightgbm: 4.1.0 +2023-11-09 11:35:31,540:INFO: numba: 0.58.1 +2023-11-09 11:35:31,540:INFO: requests: 2.31.0 +2023-11-09 11:35:31,540:INFO: matplotlib: 3.7.3 +2023-11-09 11:35:31,540:INFO: scikitplot: 0.3.7 +2023-11-09 11:35:31,540:INFO: yellowbrick: 1.5 +2023-11-09 11:35:31,540:INFO: plotly: 5.18.0 +2023-11-09 11:35:31,540:INFO: plotly-resampler: Not installed +2023-11-09 11:35:31,540:INFO: kaleido: 0.2.1 +2023-11-09 11:35:31,541:INFO: schemdraw: 0.15 +2023-11-09 11:35:31,541:INFO: statsmodels: 0.14.0 +2023-11-09 11:35:31,541:INFO: sktime: 0.21.1 +2023-11-09 11:35:31,541:INFO: tbats: 1.1.3 +2023-11-09 11:35:31,541:INFO: pmdarima: 2.0.4 +2023-11-09 11:35:31,541:INFO: psutil: 5.9.0 +2023-11-09 11:35:31,541:INFO: markupsafe: 2.1.3 +2023-11-09 11:35:31,541:INFO: pickle5: Not installed +2023-11-09 11:35:31,541:INFO: cloudpickle: 3.0.0 +2023-11-09 11:35:31,541:INFO: deprecation: 2.1.0 +2023-11-09 11:35:31,541:INFO: xxhash: 3.4.1 +2023-11-09 11:35:31,541:INFO: wurlitzer: 3.0.3 +2023-11-09 11:35:31,541:INFO:PyCaret optional dependencies: +2023-11-09 11:35:31,541:INFO: shap: Not installed +2023-11-09 11:35:31,541:INFO: interpret: Not installed +2023-11-09 11:35:31,541:INFO: umap: Not installed +2023-11-09 11:35:31,541:INFO: ydata_profiling: Not installed +2023-11-09 11:35:31,541:INFO: explainerdashboard: Not installed +2023-11-09 11:35:31,541:INFO: autoviz: Not installed +2023-11-09 11:35:31,541:INFO: fairlearn: Not installed +2023-11-09 11:35:31,542:INFO: deepchecks: Not installed +2023-11-09 11:35:31,542:INFO: xgboost: Not installed +2023-11-09 11:35:31,542:INFO: catboost: Not installed +2023-11-09 11:35:31,542:INFO: kmodes: Not installed +2023-11-09 11:35:31,542:INFO: mlxtend: Not installed +2023-11-09 11:35:31,542:INFO: statsforecast: Not installed +2023-11-09 11:35:31,542:INFO: tune_sklearn: Not installed +2023-11-09 11:35:31,542:INFO: ray: Not installed +2023-11-09 11:35:31,542:INFO: hyperopt: Not installed +2023-11-09 11:35:31,542:INFO: optuna: Not installed +2023-11-09 11:35:31,542:INFO: skopt: Not installed +2023-11-09 11:35:31,542:INFO: mlflow: Not installed +2023-11-09 11:35:31,542:INFO: gradio: Not installed +2023-11-09 11:35:31,542:INFO: fastapi: Not installed +2023-11-09 11:35:31,542:INFO: uvicorn: Not installed +2023-11-09 11:35:31,542:INFO: m2cgen: Not installed +2023-11-09 11:35:31,542:INFO: evidently: Not installed +2023-11-09 11:35:31,542:INFO: fugue: Not installed +2023-11-09 11:35:31,542:INFO: streamlit: Not installed +2023-11-09 11:35:31,542:INFO: prophet: Not installed +2023-11-09 11:35:31,543:INFO:None +2023-11-09 11:35:31,543:INFO:Set up data. +2023-11-09 11:35:31,546:INFO:Set up folding strategy. +2023-11-09 11:36:45,987:INFO:PyCaret RegressionExperiment +2023-11-09 11:36:45,987:INFO:Logging name: reg-default-name +2023-11-09 11:36:45,987:INFO:ML Usecase: MLUsecase.REGRESSION +2023-11-09 11:36:45,988:INFO:version 3.1.0 +2023-11-09 11:36:45,988:INFO:Initializing setup() +2023-11-09 11:36:45,988:INFO:self.USI: 203d +2023-11-09 11:36:45,988:INFO:self._variable_keys: {'seed', 'idx', 'transform_target_param', 'gpu_param', 'target_param', 'log_plots_param', 'pipeline', 'logging_param', 'fold_groups_param', '_ml_usecase', 'html_param', 'gpu_n_jobs_param', 'y', 'y_test', 'y_train', 'memory', 'exp_id', 'X_test', 'exp_name_log', 'USI', 'data', 'X_train', 'fold_shuffle_param', 'X', 'fold_generator', 'n_jobs_param', '_available_plots'} +2023-11-09 11:36:45,988:INFO:Checking environment +2023-11-09 11:36:45,988:INFO:python_version: 3.8.18 +2023-11-09 11:36:45,988:INFO:python_build: ('default', 'Sep 11 2023 13:40:15') +2023-11-09 11:36:45,988:INFO:machine: x86_64 +2023-11-09 11:36:45,988:INFO:platform: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:36:45,988:INFO:Memory: svmem(total=8315187200, available=4864962560, percent=41.5, used=3115589632, free=486223872, active=1479172096, inactive=5535469568, buffers=342929408, cached=4370444288, shared=4476928, slab=650862592) +2023-11-09 11:36:45,989:INFO:Physical Core: 1 +2023-11-09 11:36:45,989:INFO:Logical Core: 2 +2023-11-09 11:36:45,989:INFO:Checking libraries +2023-11-09 11:36:45,989:INFO:System: +2023-11-09 11:36:45,989:INFO: python: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] +2023-11-09 11:36:45,989:INFO:executable: /workspaces/D2I-Jupyter-Notebook-Tools/.conda/bin/python +2023-11-09 11:36:45,989:INFO: machine: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:36:45,989:INFO:PyCaret required dependencies: +2023-11-09 11:36:45,989:INFO: pip: 23.3 +2023-11-09 11:36:45,989:INFO: setuptools: 68.0.0 +2023-11-09 11:36:45,989:INFO: pycaret: 3.1.0 +2023-11-09 11:36:45,989:INFO: IPython: 8.12.0 +2023-11-09 11:36:45,989:INFO: ipywidgets: 8.1.1 +2023-11-09 11:36:45,989:INFO: tqdm: 4.66.1 +2023-11-09 11:36:45,989:INFO: numpy: 1.23.5 +2023-11-09 11:36:45,989:INFO: pandas: 1.5.3 +2023-11-09 11:36:45,989:INFO: jinja2: 3.1.2 +2023-11-09 11:36:45,989:INFO: scipy: 1.10.1 +2023-11-09 11:36:45,990:INFO: joblib: 1.3.2 +2023-11-09 11:36:45,990:INFO: sklearn: 1.2.2 +2023-11-09 11:36:45,990:INFO: pyod: 1.1.1 +2023-11-09 11:36:45,990:INFO: imblearn: 0.11.0 +2023-11-09 11:36:45,990:INFO: category_encoders: 2.6.3 +2023-11-09 11:36:45,990:INFO: lightgbm: 4.1.0 +2023-11-09 11:36:45,990:INFO: numba: 0.58.1 +2023-11-09 11:36:45,990:INFO: requests: 2.31.0 +2023-11-09 11:36:45,990:INFO: matplotlib: 3.7.3 +2023-11-09 11:36:45,990:INFO: scikitplot: 0.3.7 +2023-11-09 11:36:45,990:INFO: yellowbrick: 1.5 +2023-11-09 11:36:45,990:INFO: plotly: 5.18.0 +2023-11-09 11:36:45,990:INFO: plotly-resampler: Not installed +2023-11-09 11:36:45,990:INFO: kaleido: 0.2.1 +2023-11-09 11:36:45,990:INFO: schemdraw: 0.15 +2023-11-09 11:36:45,990:INFO: statsmodels: 0.14.0 +2023-11-09 11:36:45,990:INFO: sktime: 0.21.1 +2023-11-09 11:36:45,990:INFO: tbats: 1.1.3 +2023-11-09 11:36:45,990:INFO: pmdarima: 2.0.4 +2023-11-09 11:36:45,990:INFO: psutil: 5.9.0 +2023-11-09 11:36:45,990:INFO: markupsafe: 2.1.3 +2023-11-09 11:36:45,990:INFO: pickle5: Not installed +2023-11-09 11:36:45,990:INFO: cloudpickle: 3.0.0 +2023-11-09 11:36:45,990:INFO: deprecation: 2.1.0 +2023-11-09 11:36:45,990:INFO: xxhash: 3.4.1 +2023-11-09 11:36:45,990:INFO: wurlitzer: 3.0.3 +2023-11-09 11:36:45,990:INFO:PyCaret optional dependencies: +2023-11-09 11:36:45,990:INFO: shap: Not installed +2023-11-09 11:36:45,991:INFO: interpret: Not installed +2023-11-09 11:36:45,991:INFO: umap: Not installed +2023-11-09 11:36:45,991:INFO: ydata_profiling: Not installed +2023-11-09 11:36:45,991:INFO: explainerdashboard: Not installed +2023-11-09 11:36:45,991:INFO: autoviz: Not installed +2023-11-09 11:36:45,991:INFO: fairlearn: Not installed +2023-11-09 11:36:45,991:INFO: deepchecks: Not installed +2023-11-09 11:36:45,991:INFO: xgboost: Not installed +2023-11-09 11:36:45,991:INFO: catboost: Not installed +2023-11-09 11:36:45,991:INFO: kmodes: Not installed +2023-11-09 11:36:45,991:INFO: mlxtend: Not installed +2023-11-09 11:36:45,991:INFO: statsforecast: Not installed +2023-11-09 11:36:45,991:INFO: tune_sklearn: Not installed +2023-11-09 11:36:45,991:INFO: ray: Not installed +2023-11-09 11:36:45,991:INFO: hyperopt: Not installed +2023-11-09 11:36:45,991:INFO: optuna: Not installed +2023-11-09 11:36:45,991:INFO: skopt: Not installed +2023-11-09 11:36:45,991:INFO: mlflow: Not installed +2023-11-09 11:36:45,991:INFO: gradio: Not installed +2023-11-09 11:36:45,991:INFO: fastapi: Not installed +2023-11-09 11:36:45,991:INFO: uvicorn: Not installed +2023-11-09 11:36:45,991:INFO: m2cgen: Not installed +2023-11-09 11:36:45,991:INFO: evidently: Not installed +2023-11-09 11:36:45,991:INFO: fugue: Not installed +2023-11-09 11:36:45,991:INFO: streamlit: Not installed +2023-11-09 11:36:45,991:INFO: prophet: Not installed +2023-11-09 11:36:45,991:INFO:None +2023-11-09 11:36:45,991:INFO:Set up data. +2023-11-09 11:36:45,995:INFO:Set up folding strategy. +2023-11-09 11:36:45,995:INFO:Set up train/test split. +2023-11-09 11:36:45,995:INFO:Set up data. +2023-11-09 11:36:45,998:INFO:Set up index. +2023-11-09 11:36:45,998:INFO:Assigning column types. +2023-11-09 11:36:46,001:INFO:Engine successfully changes for model 'lr' to 'sklearn'. +2023-11-09 11:36:46,001:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,006:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,009:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,099:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,154:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,155:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,155:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,155:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,159:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,163:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,211:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,249:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,249:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,250:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,250:INFO:Engine successfully changes for model 'lasso' to 'sklearn'. +2023-11-09 11:36:46,254:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,258:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,306:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,343:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,344:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,344:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,348:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,352:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,399:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,436:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,436:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,437:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,437:INFO:Engine successfully changes for model 'ridge' to 'sklearn'. +2023-11-09 11:36:46,444:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,491:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,529:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,529:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,530:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,538:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,585:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,621:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,622:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,622:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,623:INFO:Engine successfully changes for model 'en' to 'sklearn'. +2023-11-09 11:36:46,680:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,717:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,717:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,717:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,781:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,824:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,825:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,825:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,826:INFO:Engine successfully changes for model 'knn' to 'sklearn'. +2023-11-09 11:36:46,881:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:36:46,922:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,922:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:46,979:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:36:47,017:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:47,018:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:47,018:INFO:Engine successfully changes for model 'svm' to 'sklearn'. +2023-11-09 11:36:47,113:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:47,113:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:47,215:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:47,216:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:47,217:INFO:Preparing preprocessing pipeline... +2023-11-09 11:36:47,217:INFO:Set up target transformation. +2023-11-09 11:36:47,217:INFO:Set up simple imputation. +2023-11-09 11:36:47,217:INFO:Set up column name cleaning. +2023-11-09 11:36:47,246:INFO:Finished creating preprocessing pipeline. +2023-11-09 11:36:47,252:INFO:Pipeline: Pipeline(memory=FastMemory(location=/tmp/joblib), + steps=[('target_transformation', + TransformerWrapperWithInverse(transformer=TargetTransformer(estimator=PowerTransformer(standardize=False)))), + ('numerical_imputer', + TransformerWrapper(include=['Year'], + transformer=SimpleImputer())), + ('categorical_imputer', + TransformerWrapper(include=[], + transformer=SimpleImputer(strategy='most_frequent'))), + ('clean_column_names', + TransformerWrapper(transformer=CleanColumnNames()))]) +2023-11-09 11:36:47,252:INFO:Creating final display dataframe. +2023-11-09 11:36:47,321:INFO:Setup _display_container: Description Value +0 Session id 123 +1 Target Average price All property types +2 Target type Regression +3 Original data shape (523, 4) +4 Transformed data shape (523, 4) +5 Transformed train set shape (372, 4) +6 Transformed test set shape (151, 4) +7 Numeric features 1 +8 Preprocess True +9 Imputation type simple +10 Numeric imputation mean +11 Categorical imputation mode +12 Transform target True +13 Transform target method yeo-johnson +14 Fold Generator TimeSeriesSplit +15 Fold Number 3 +16 CPU Jobs -1 +17 Use GPU False +18 Log Experiment False +19 Experiment Name reg-default-name +20 USI 203d +2023-11-09 11:36:47,421:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:47,422:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:47,551:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:47,551:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:36:47,552:INFO:setup() successfully completed in 1.57s............... +2023-11-09 11:38:34,527:INFO:PyCaret RegressionExperiment +2023-11-09 11:38:34,527:INFO:Logging name: reg-default-name +2023-11-09 11:38:34,527:INFO:ML Usecase: MLUsecase.REGRESSION +2023-11-09 11:38:34,527:INFO:version 3.1.0 +2023-11-09 11:38:34,527:INFO:Initializing setup() +2023-11-09 11:38:34,528:INFO:self.USI: c357 +2023-11-09 11:38:34,528:INFO:self._variable_keys: {'seed', 'idx', 'transform_target_param', 'gpu_param', 'target_param', 'log_plots_param', 'pipeline', 'logging_param', 'fold_groups_param', '_ml_usecase', 'html_param', 'gpu_n_jobs_param', 'y', 'y_test', 'y_train', 'memory', 'exp_id', 'X_test', 'exp_name_log', 'USI', 'data', 'X_train', 'fold_shuffle_param', 'X', 'fold_generator', 'n_jobs_param', '_available_plots'} +2023-11-09 11:38:34,528:INFO:Checking environment +2023-11-09 11:38:34,528:INFO:python_version: 3.8.18 +2023-11-09 11:38:34,528:INFO:python_build: ('default', 'Sep 11 2023 13:40:15') +2023-11-09 11:38:34,528:INFO:machine: x86_64 +2023-11-09 11:38:34,529:INFO:platform: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:38:34,529:INFO:Memory: svmem(total=8315187200, available=4770590720, percent=42.6, used=3209961472, free=386134016, active=1480335360, inactive=5612920832, buffers=343781376, cached=4375310336, shared=4476928, slab=650903552) +2023-11-09 11:38:34,529:INFO:Physical Core: 1 +2023-11-09 11:38:34,529:INFO:Logical Core: 2 +2023-11-09 11:38:34,529:INFO:Checking libraries +2023-11-09 11:38:34,529:INFO:System: +2023-11-09 11:38:34,529:INFO: python: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] +2023-11-09 11:38:34,529:INFO:executable: /workspaces/D2I-Jupyter-Notebook-Tools/.conda/bin/python +2023-11-09 11:38:34,529:INFO: machine: Linux-6.2.0-1015-azure-x86_64-with-glibc2.17 +2023-11-09 11:38:34,530:INFO:PyCaret required dependencies: +2023-11-09 11:38:34,530:INFO: pip: 23.3 +2023-11-09 11:38:34,530:INFO: setuptools: 68.0.0 +2023-11-09 11:38:34,530:INFO: pycaret: 3.1.0 +2023-11-09 11:38:34,530:INFO: IPython: 8.12.0 +2023-11-09 11:38:34,530:INFO: ipywidgets: 8.1.1 +2023-11-09 11:38:34,531:INFO: tqdm: 4.66.1 +2023-11-09 11:38:34,531:INFO: numpy: 1.23.5 +2023-11-09 11:38:34,531:INFO: pandas: 1.5.3 +2023-11-09 11:38:34,531:INFO: jinja2: 3.1.2 +2023-11-09 11:38:34,531:INFO: scipy: 1.10.1 +2023-11-09 11:38:34,531:INFO: joblib: 1.3.2 +2023-11-09 11:38:34,531:INFO: sklearn: 1.2.2 +2023-11-09 11:38:34,531:INFO: pyod: 1.1.1 +2023-11-09 11:38:34,531:INFO: imblearn: 0.11.0 +2023-11-09 11:38:34,531:INFO: category_encoders: 2.6.3 +2023-11-09 11:38:34,531:INFO: lightgbm: 4.1.0 +2023-11-09 11:38:34,531:INFO: numba: 0.58.1 +2023-11-09 11:38:34,531:INFO: requests: 2.31.0 +2023-11-09 11:38:34,532:INFO: matplotlib: 3.7.3 +2023-11-09 11:38:34,532:INFO: scikitplot: 0.3.7 +2023-11-09 11:38:34,532:INFO: yellowbrick: 1.5 +2023-11-09 11:38:34,532:INFO: plotly: 5.18.0 +2023-11-09 11:38:34,532:INFO: plotly-resampler: Not installed +2023-11-09 11:38:34,532:INFO: kaleido: 0.2.1 +2023-11-09 11:38:34,532:INFO: schemdraw: 0.15 +2023-11-09 11:38:34,532:INFO: statsmodels: 0.14.0 +2023-11-09 11:38:34,532:INFO: sktime: 0.21.1 +2023-11-09 11:38:34,533:INFO: tbats: 1.1.3 +2023-11-09 11:38:34,533:INFO: pmdarima: 2.0.4 +2023-11-09 11:38:34,533:INFO: psutil: 5.9.0 +2023-11-09 11:38:34,533:INFO: markupsafe: 2.1.3 +2023-11-09 11:38:34,533:INFO: pickle5: Not installed +2023-11-09 11:38:34,533:INFO: cloudpickle: 3.0.0 +2023-11-09 11:38:34,533:INFO: deprecation: 2.1.0 +2023-11-09 11:38:34,533:INFO: xxhash: 3.4.1 +2023-11-09 11:38:34,533:INFO: wurlitzer: 3.0.3 +2023-11-09 11:38:34,533:INFO:PyCaret optional dependencies: +2023-11-09 11:38:34,533:INFO: shap: Not installed +2023-11-09 11:38:34,533:INFO: interpret: Not installed +2023-11-09 11:38:34,533:INFO: umap: Not installed +2023-11-09 11:38:34,533:INFO: ydata_profiling: Not installed +2023-11-09 11:38:34,533:INFO: explainerdashboard: Not installed +2023-11-09 11:38:34,533:INFO: autoviz: Not installed +2023-11-09 11:38:34,533:INFO: fairlearn: Not installed +2023-11-09 11:38:34,533:INFO: deepchecks: Not installed +2023-11-09 11:38:34,533:INFO: xgboost: Not installed +2023-11-09 11:38:34,534:INFO: catboost: Not installed +2023-11-09 11:38:34,534:INFO: kmodes: Not installed +2023-11-09 11:38:34,534:INFO: mlxtend: Not installed +2023-11-09 11:38:34,534:INFO: statsforecast: Not installed +2023-11-09 11:38:34,534:INFO: tune_sklearn: Not installed +2023-11-09 11:38:34,534:INFO: ray: Not installed +2023-11-09 11:38:34,534:INFO: hyperopt: Not installed +2023-11-09 11:38:34,534:INFO: optuna: Not installed +2023-11-09 11:38:34,534:INFO: skopt: Not installed +2023-11-09 11:38:34,534:INFO: mlflow: Not installed +2023-11-09 11:38:34,534:INFO: gradio: Not installed +2023-11-09 11:38:34,534:INFO: fastapi: Not installed +2023-11-09 11:38:34,534:INFO: uvicorn: Not installed +2023-11-09 11:38:34,534:INFO: m2cgen: Not installed +2023-11-09 11:38:34,534:INFO: evidently: Not installed +2023-11-09 11:38:34,534:INFO: fugue: Not installed +2023-11-09 11:38:34,534:INFO: streamlit: Not installed +2023-11-09 11:38:34,534:INFO: prophet: Not installed +2023-11-09 11:38:34,534:INFO:None +2023-11-09 11:38:34,534:INFO:Set up data. +2023-11-09 11:38:34,538:INFO:Set up folding strategy. +2023-11-09 11:38:34,538:INFO:Set up train/test split. +2023-11-09 11:38:34,540:INFO:Set up index. +2023-11-09 11:38:34,541:INFO:Assigning column types. +2023-11-09 11:38:34,543:INFO:Engine successfully changes for model 'lr' to 'sklearn'. +2023-11-09 11:38:34,543:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,547:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,551:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,604:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,642:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,643:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:34,643:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:34,644:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,648:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,652:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,702:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,740:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,741:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:34,741:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:34,741:INFO:Engine successfully changes for model 'lasso' to 'sklearn'. +2023-11-09 11:38:34,745:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,749:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,798:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,837:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,838:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:34,838:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:34,842:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,846:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,897:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,935:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,935:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:34,936:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:34,936:INFO:Engine successfully changes for model 'ridge' to 'sklearn'. +2023-11-09 11:38:34,943:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:38:34,994:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:38:35,033:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:38:35,033:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,033:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,041:INFO:Engine for model 'en' has not been set explicitly, hence returning None. +2023-11-09 11:38:35,089:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:38:35,129:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:38:35,129:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,130:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,130:INFO:Engine successfully changes for model 'en' to 'sklearn'. +2023-11-09 11:38:35,187:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:38:35,225:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:38:35,229:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,229:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,290:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:38:35,338:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. +2023-11-09 11:38:35,339:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,339:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,339:INFO:Engine successfully changes for model 'knn' to 'sklearn'. +2023-11-09 11:38:35,394:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:38:35,432:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,432:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,487:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. +2023-11-09 11:38:35,526:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,526:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,527:INFO:Engine successfully changes for model 'svm' to 'sklearn'. +2023-11-09 11:38:35,637:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,637:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,820:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,820:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:35,821:INFO:Preparing preprocessing pipeline... +2023-11-09 11:38:35,821:INFO:Set up target transformation. +2023-11-09 11:38:35,821:INFO:Set up simple imputation. +2023-11-09 11:38:35,822:INFO:Set up column name cleaning. +2023-11-09 11:38:35,861:INFO:Finished creating preprocessing pipeline. +2023-11-09 11:38:35,870:INFO:Pipeline: Pipeline(memory=FastMemory(location=/tmp/joblib), + steps=[('target_transformation', + TransformerWrapperWithInverse(transformer=TargetTransformer(estimator=PowerTransformer(standardize=False)))), + ('numerical_imputer', + TransformerWrapper(include=['Year'], + transformer=SimpleImputer())), + ('categorical_imputer', + TransformerWrapper(include=[], + transformer=SimpleImputer(strategy='most_frequent'))), + ('clean_column_names', + TransformerWrapper(transformer=CleanColumnNames()))]) +2023-11-09 11:38:35,874:INFO:Creating final display dataframe. +2023-11-09 11:38:35,992:INFO:Setup _display_container: Description Value +0 Session id 123 +1 Target Average price All property types +2 Target type Regression +3 Original data shape (372, 4) +4 Transformed data shape (372, 4) +5 Transformed train set shape (260, 4) +6 Transformed test set shape (112, 4) +7 Numeric features 1 +8 Preprocess True +9 Imputation type simple +10 Numeric imputation mean +11 Categorical imputation mode +12 Transform target True +13 Transform target method yeo-johnson +14 Fold Generator TimeSeriesSplit +15 Fold Number 3 +16 CPU Jobs -1 +17 Use GPU False +18 Log Experiment False +19 Experiment Name reg-default-name +20 USI c357 +2023-11-09 11:38:36,261:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:36,262:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:36,367:WARNING: +'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:36,368:WARNING: +'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. +Alternately, you can install this by running `pip install pycaret[models]` +2023-11-09 11:38:36,368:INFO:setup() successfully completed in 1.84s............... +2023-11-09 11:38:40,958:INFO:Initializing compare_models() +2023-11-09 11:38:40,959:INFO:compare_models(self=, include=None, fold=None, round=4, cross_validation=True, sort=MAE, n_select=1, budget_time=None, turbo=True, errors=ignore, fit_kwargs=None, groups=None, experiment_custom_tags=None, probability_threshold=None, verbose=True, parallel=None, caller_params={'self': , 'include': None, 'exclude': None, 'fold': None, 'round': 4, 'cross_validation': True, 'sort': 'MAE', 'n_select': 1, 'budget_time': None, 'turbo': True, 'errors': 'ignore', 'fit_kwargs': None, 'groups': None, 'experiment_custom_tags': None, 'engine': None, 'verbose': True, 'parallel': None, '__class__': }, exclude=None) +2023-11-09 11:38:40,959:INFO:Checking exceptions +2023-11-09 11:38:40,961:INFO:Preparing display monitor +2023-11-09 11:38:40,984:INFO:Initializing Linear Regression +2023-11-09 11:38:40,984:INFO:Total runtime is 3.62396240234375e-06 minutes +2023-11-09 11:38:40,987:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:40,988:INFO:Initializing create_model() +2023-11-09 11:38:40,988:INFO:create_model(self=, estimator=lr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:40,988:INFO:Checking exceptions +2023-11-09 11:38:40,988:INFO:Importing libraries +2023-11-09 11:38:40,988:INFO:Copying training dataset +2023-11-09 11:38:40,992:INFO:Defining folds +2023-11-09 11:38:40,992:INFO:Declaring metric variables +2023-11-09 11:38:40,996:INFO:Importing untrained model +2023-11-09 11:38:41,000:INFO:Linear Regression Imported successfully +2023-11-09 11:38:41,010:INFO:Starting cross validation +2023-11-09 11:38:41,011:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:42,960:INFO:Calculating mean and std +2023-11-09 11:38:42,962:INFO:Creating metrics dataframe +2023-11-09 11:38:42,973:INFO:Uploading results into container +2023-11-09 11:38:42,973:INFO:Uploading model into container now +2023-11-09 11:38:42,976:INFO:_master_model_container: 1 +2023-11-09 11:38:42,976:INFO:_display_container: 2 +2023-11-09 11:38:42,977:INFO:LinearRegression(n_jobs=-1) +2023-11-09 11:38:42,977:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:43,138:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:43,138:INFO:Creating metrics dataframe +2023-11-09 11:38:43,152:INFO:Initializing Lasso Regression +2023-11-09 11:38:43,152:INFO:Total runtime is 0.03613371849060059 minutes +2023-11-09 11:38:43,156:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:43,157:INFO:Initializing create_model() +2023-11-09 11:38:43,157:INFO:create_model(self=, estimator=lasso, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:43,157:INFO:Checking exceptions +2023-11-09 11:38:43,157:INFO:Importing libraries +2023-11-09 11:38:43,157:INFO:Copying training dataset +2023-11-09 11:38:43,162:INFO:Defining folds +2023-11-09 11:38:43,162:INFO:Declaring metric variables +2023-11-09 11:38:43,166:INFO:Importing untrained model +2023-11-09 11:38:43,169:INFO:Lasso Regression Imported successfully +2023-11-09 11:38:43,176:INFO:Starting cross validation +2023-11-09 11:38:43,177:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:43,255:INFO:Calculating mean and std +2023-11-09 11:38:43,256:INFO:Creating metrics dataframe +2023-11-09 11:38:43,258:INFO:Uploading results into container +2023-11-09 11:38:43,259:INFO:Uploading model into container now +2023-11-09 11:38:43,259:INFO:_master_model_container: 2 +2023-11-09 11:38:43,259:INFO:_display_container: 2 +2023-11-09 11:38:43,259:INFO:Lasso(random_state=123) +2023-11-09 11:38:43,260:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:43,392:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:43,392:INFO:Creating metrics dataframe +2023-11-09 11:38:43,400:INFO:Initializing Ridge Regression +2023-11-09 11:38:43,401:INFO:Total runtime is 0.04028120835622152 minutes +2023-11-09 11:38:43,404:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:43,404:INFO:Initializing create_model() +2023-11-09 11:38:43,405:INFO:create_model(self=, estimator=ridge, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:43,405:INFO:Checking exceptions +2023-11-09 11:38:43,405:INFO:Importing libraries +2023-11-09 11:38:43,405:INFO:Copying training dataset +2023-11-09 11:38:43,408:INFO:Defining folds +2023-11-09 11:38:43,408:INFO:Declaring metric variables +2023-11-09 11:38:43,412:INFO:Importing untrained model +2023-11-09 11:38:43,415:INFO:Ridge Regression Imported successfully +2023-11-09 11:38:43,421:INFO:Starting cross validation +2023-11-09 11:38:43,422:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:43,527:INFO:Calculating mean and std +2023-11-09 11:38:43,529:INFO:Creating metrics dataframe +2023-11-09 11:38:43,532:INFO:Uploading results into container +2023-11-09 11:38:43,534:INFO:Uploading model into container now +2023-11-09 11:38:43,535:INFO:_master_model_container: 3 +2023-11-09 11:38:43,535:INFO:_display_container: 2 +2023-11-09 11:38:43,536:INFO:Ridge(random_state=123) +2023-11-09 11:38:43,536:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:43,700:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:43,700:INFO:Creating metrics dataframe +2023-11-09 11:38:43,713:INFO:Initializing Elastic Net +2023-11-09 11:38:43,713:INFO:Total runtime is 0.045483875274658206 minutes +2023-11-09 11:38:43,716:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:43,717:INFO:Initializing create_model() +2023-11-09 11:38:43,717:INFO:create_model(self=, estimator=en, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:43,717:INFO:Checking exceptions +2023-11-09 11:38:43,717:INFO:Importing libraries +2023-11-09 11:38:43,718:INFO:Copying training dataset +2023-11-09 11:38:43,722:INFO:Defining folds +2023-11-09 11:38:43,722:INFO:Declaring metric variables +2023-11-09 11:38:43,727:INFO:Importing untrained model +2023-11-09 11:38:43,731:INFO:Elastic Net Imported successfully +2023-11-09 11:38:43,738:INFO:Starting cross validation +2023-11-09 11:38:43,739:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:43,815:INFO:Calculating mean and std +2023-11-09 11:38:43,815:INFO:Creating metrics dataframe +2023-11-09 11:38:43,818:INFO:Uploading results into container +2023-11-09 11:38:43,818:INFO:Uploading model into container now +2023-11-09 11:38:43,818:INFO:_master_model_container: 4 +2023-11-09 11:38:43,818:INFO:_display_container: 2 +2023-11-09 11:38:43,819:INFO:ElasticNet(random_state=123) +2023-11-09 11:38:43,819:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:43,958:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:43,959:INFO:Creating metrics dataframe +2023-11-09 11:38:43,967:INFO:Initializing Least Angle Regression +2023-11-09 11:38:43,967:INFO:Total runtime is 0.049719901879628506 minutes +2023-11-09 11:38:43,970:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:43,971:INFO:Initializing create_model() +2023-11-09 11:38:43,971:INFO:create_model(self=, estimator=lar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:43,971:INFO:Checking exceptions +2023-11-09 11:38:43,971:INFO:Importing libraries +2023-11-09 11:38:43,971:INFO:Copying training dataset +2023-11-09 11:38:43,974:INFO:Defining folds +2023-11-09 11:38:43,975:INFO:Declaring metric variables +2023-11-09 11:38:43,979:INFO:Importing untrained model +2023-11-09 11:38:43,982:INFO:Least Angle Regression Imported successfully +2023-11-09 11:38:43,988:INFO:Starting cross validation +2023-11-09 11:38:43,989:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:44,069:INFO:Calculating mean and std +2023-11-09 11:38:44,069:INFO:Creating metrics dataframe +2023-11-09 11:38:44,072:INFO:Uploading results into container +2023-11-09 11:38:44,073:INFO:Uploading model into container now +2023-11-09 11:38:44,073:INFO:_master_model_container: 5 +2023-11-09 11:38:44,073:INFO:_display_container: 2 +2023-11-09 11:38:44,073:INFO:Lars(random_state=123) +2023-11-09 11:38:44,073:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:44,199:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:44,199:INFO:Creating metrics dataframe +2023-11-09 11:38:44,209:INFO:Initializing Lasso Least Angle Regression +2023-11-09 11:38:44,209:INFO:Total runtime is 0.05375015338261923 minutes +2023-11-09 11:38:44,212:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:44,212:INFO:Initializing create_model() +2023-11-09 11:38:44,213:INFO:create_model(self=, estimator=llar, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:44,213:INFO:Checking exceptions +2023-11-09 11:38:44,213:INFO:Importing libraries +2023-11-09 11:38:44,213:INFO:Copying training dataset +2023-11-09 11:38:44,216:INFO:Defining folds +2023-11-09 11:38:44,217:INFO:Declaring metric variables +2023-11-09 11:38:44,220:INFO:Importing untrained model +2023-11-09 11:38:44,223:INFO:Lasso Least Angle Regression Imported successfully +2023-11-09 11:38:44,229:INFO:Starting cross validation +2023-11-09 11:38:44,229:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:44,307:INFO:Calculating mean and std +2023-11-09 11:38:44,307:INFO:Creating metrics dataframe +2023-11-09 11:38:44,310:INFO:Uploading results into container +2023-11-09 11:38:44,311:INFO:Uploading model into container now +2023-11-09 11:38:44,312:INFO:_master_model_container: 6 +2023-11-09 11:38:44,312:INFO:_display_container: 2 +2023-11-09 11:38:44,312:INFO:LassoLars(random_state=123) +2023-11-09 11:38:44,312:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:44,441:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:44,441:INFO:Creating metrics dataframe +2023-11-09 11:38:44,450:INFO:Initializing Orthogonal Matching Pursuit +2023-11-09 11:38:44,450:INFO:Total runtime is 0.05777235428492229 minutes +2023-11-09 11:38:44,453:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:44,454:INFO:Initializing create_model() +2023-11-09 11:38:44,454:INFO:create_model(self=, estimator=omp, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:44,454:INFO:Checking exceptions +2023-11-09 11:38:44,454:INFO:Importing libraries +2023-11-09 11:38:44,454:INFO:Copying training dataset +2023-11-09 11:38:44,459:INFO:Defining folds +2023-11-09 11:38:44,459:INFO:Declaring metric variables +2023-11-09 11:38:44,462:INFO:Importing untrained model +2023-11-09 11:38:44,465:INFO:Orthogonal Matching Pursuit Imported successfully +2023-11-09 11:38:44,471:INFO:Starting cross validation +2023-11-09 11:38:44,472:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:44,558:INFO:Calculating mean and std +2023-11-09 11:38:44,559:INFO:Creating metrics dataframe +2023-11-09 11:38:44,563:INFO:Uploading results into container +2023-11-09 11:38:44,563:INFO:Uploading model into container now +2023-11-09 11:38:44,564:INFO:_master_model_container: 7 +2023-11-09 11:38:44,564:INFO:_display_container: 2 +2023-11-09 11:38:44,564:INFO:OrthogonalMatchingPursuit() +2023-11-09 11:38:44,564:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:44,708:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:44,708:INFO:Creating metrics dataframe +2023-11-09 11:38:44,723:INFO:Initializing Bayesian Ridge +2023-11-09 11:38:44,723:INFO:Total runtime is 0.06232144832611085 minutes +2023-11-09 11:38:44,726:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:44,727:INFO:Initializing create_model() +2023-11-09 11:38:44,727:INFO:create_model(self=, estimator=br, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:44,727:INFO:Checking exceptions +2023-11-09 11:38:44,727:INFO:Importing libraries +2023-11-09 11:38:44,727:INFO:Copying training dataset +2023-11-09 11:38:44,731:INFO:Defining folds +2023-11-09 11:38:44,731:INFO:Declaring metric variables +2023-11-09 11:38:44,735:INFO:Importing untrained model +2023-11-09 11:38:44,738:INFO:Bayesian Ridge Imported successfully +2023-11-09 11:38:44,744:INFO:Starting cross validation +2023-11-09 11:38:44,745:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:44,830:INFO:Calculating mean and std +2023-11-09 11:38:44,831:INFO:Creating metrics dataframe +2023-11-09 11:38:44,834:INFO:Uploading results into container +2023-11-09 11:38:44,835:INFO:Uploading model into container now +2023-11-09 11:38:44,836:INFO:_master_model_container: 8 +2023-11-09 11:38:44,836:INFO:_display_container: 2 +2023-11-09 11:38:44,837:INFO:BayesianRidge() +2023-11-09 11:38:44,837:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:44,976:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:44,976:INFO:Creating metrics dataframe +2023-11-09 11:38:44,985:INFO:Initializing Passive Aggressive Regressor +2023-11-09 11:38:44,986:INFO:Total runtime is 0.06669942935307821 minutes +2023-11-09 11:38:44,989:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:44,990:INFO:Initializing create_model() +2023-11-09 11:38:44,990:INFO:create_model(self=, estimator=par, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:44,990:INFO:Checking exceptions +2023-11-09 11:38:44,990:INFO:Importing libraries +2023-11-09 11:38:44,990:INFO:Copying training dataset +2023-11-09 11:38:44,995:INFO:Defining folds +2023-11-09 11:38:44,995:INFO:Declaring metric variables +2023-11-09 11:38:44,999:INFO:Importing untrained model +2023-11-09 11:38:45,003:INFO:Passive Aggressive Regressor Imported successfully +2023-11-09 11:38:45,010:INFO:Starting cross validation +2023-11-09 11:38:45,012:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:45,087:INFO:Calculating mean and std +2023-11-09 11:38:45,088:INFO:Creating metrics dataframe +2023-11-09 11:38:45,090:INFO:Uploading results into container +2023-11-09 11:38:45,091:INFO:Uploading model into container now +2023-11-09 11:38:45,091:INFO:_master_model_container: 9 +2023-11-09 11:38:45,091:INFO:_display_container: 2 +2023-11-09 11:38:45,092:INFO:PassiveAggressiveRegressor(random_state=123) +2023-11-09 11:38:45,092:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:45,226:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:45,226:INFO:Creating metrics dataframe +2023-11-09 11:38:45,235:INFO:Initializing Huber Regressor +2023-11-09 11:38:45,235:INFO:Total runtime is 0.0708625078201294 minutes +2023-11-09 11:38:45,239:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:45,239:INFO:Initializing create_model() +2023-11-09 11:38:45,239:INFO:create_model(self=, estimator=huber, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:45,239:INFO:Checking exceptions +2023-11-09 11:38:45,240:INFO:Importing libraries +2023-11-09 11:38:45,240:INFO:Copying training dataset +2023-11-09 11:38:45,243:INFO:Defining folds +2023-11-09 11:38:45,244:INFO:Declaring metric variables +2023-11-09 11:38:45,247:INFO:Importing untrained model +2023-11-09 11:38:45,250:INFO:Huber Regressor Imported successfully +2023-11-09 11:38:45,256:INFO:Starting cross validation +2023-11-09 11:38:45,257:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:45,376:INFO:Calculating mean and std +2023-11-09 11:38:45,378:INFO:Creating metrics dataframe +2023-11-09 11:38:45,381:INFO:Uploading results into container +2023-11-09 11:38:45,382:INFO:Uploading model into container now +2023-11-09 11:38:45,383:INFO:_master_model_container: 10 +2023-11-09 11:38:45,383:INFO:_display_container: 2 +2023-11-09 11:38:45,383:INFO:HuberRegressor() +2023-11-09 11:38:45,383:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:45,515:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:45,516:INFO:Creating metrics dataframe +2023-11-09 11:38:45,525:INFO:Initializing K Neighbors Regressor +2023-11-09 11:38:45,525:INFO:Total runtime is 0.07569592396418254 minutes +2023-11-09 11:38:45,529:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:45,529:INFO:Initializing create_model() +2023-11-09 11:38:45,530:INFO:create_model(self=, estimator=knn, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:45,530:INFO:Checking exceptions +2023-11-09 11:38:45,530:INFO:Importing libraries +2023-11-09 11:38:45,530:INFO:Copying training dataset +2023-11-09 11:38:45,533:INFO:Defining folds +2023-11-09 11:38:45,534:INFO:Declaring metric variables +2023-11-09 11:38:45,537:INFO:Importing untrained model +2023-11-09 11:38:45,540:INFO:K Neighbors Regressor Imported successfully +2023-11-09 11:38:45,546:INFO:Starting cross validation +2023-11-09 11:38:45,547:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:45,665:INFO:Calculating mean and std +2023-11-09 11:38:45,666:INFO:Creating metrics dataframe +2023-11-09 11:38:45,670:INFO:Uploading results into container +2023-11-09 11:38:45,671:INFO:Uploading model into container now +2023-11-09 11:38:45,671:INFO:_master_model_container: 11 +2023-11-09 11:38:45,671:INFO:_display_container: 2 +2023-11-09 11:38:45,671:INFO:KNeighborsRegressor(n_jobs=-1) +2023-11-09 11:38:45,671:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:45,813:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:45,814:INFO:Creating metrics dataframe +2023-11-09 11:38:45,823:INFO:Initializing Decision Tree Regressor +2023-11-09 11:38:45,823:INFO:Total runtime is 0.0806614359219869 minutes +2023-11-09 11:38:45,827:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:45,827:INFO:Initializing create_model() +2023-11-09 11:38:45,827:INFO:create_model(self=, estimator=dt, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:45,827:INFO:Checking exceptions +2023-11-09 11:38:45,827:INFO:Importing libraries +2023-11-09 11:38:45,828:INFO:Copying training dataset +2023-11-09 11:38:45,831:INFO:Defining folds +2023-11-09 11:38:45,831:INFO:Declaring metric variables +2023-11-09 11:38:45,834:INFO:Importing untrained model +2023-11-09 11:38:45,838:INFO:Decision Tree Regressor Imported successfully +2023-11-09 11:38:45,844:INFO:Starting cross validation +2023-11-09 11:38:45,845:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:45,946:INFO:Calculating mean and std +2023-11-09 11:38:45,947:INFO:Creating metrics dataframe +2023-11-09 11:38:45,951:INFO:Uploading results into container +2023-11-09 11:38:45,954:INFO:Uploading model into container now +2023-11-09 11:38:45,955:INFO:_master_model_container: 12 +2023-11-09 11:38:45,955:INFO:_display_container: 2 +2023-11-09 11:38:45,955:INFO:DecisionTreeRegressor(random_state=123) +2023-11-09 11:38:45,955:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:46,088:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:46,088:INFO:Creating metrics dataframe +2023-11-09 11:38:46,098:INFO:Initializing Random Forest Regressor +2023-11-09 11:38:46,098:INFO:Total runtime is 0.08523745934168497 minutes +2023-11-09 11:38:46,101:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:46,102:INFO:Initializing create_model() +2023-11-09 11:38:46,102:INFO:create_model(self=, estimator=rf, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:46,102:INFO:Checking exceptions +2023-11-09 11:38:46,102:INFO:Importing libraries +2023-11-09 11:38:46,102:INFO:Copying training dataset +2023-11-09 11:38:46,105:INFO:Defining folds +2023-11-09 11:38:46,106:INFO:Declaring metric variables +2023-11-09 11:38:46,109:INFO:Importing untrained model +2023-11-09 11:38:46,113:INFO:Random Forest Regressor Imported successfully +2023-11-09 11:38:46,118:INFO:Starting cross validation +2023-11-09 11:38:46,120:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:46,704:INFO:Calculating mean and std +2023-11-09 11:38:46,705:INFO:Creating metrics dataframe +2023-11-09 11:38:46,709:INFO:Uploading results into container +2023-11-09 11:38:46,709:INFO:Uploading model into container now +2023-11-09 11:38:46,710:INFO:_master_model_container: 13 +2023-11-09 11:38:46,710:INFO:_display_container: 2 +2023-11-09 11:38:46,710:INFO:RandomForestRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:38:46,710:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:46,849:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:46,849:INFO:Creating metrics dataframe +2023-11-09 11:38:46,863:INFO:Initializing Extra Trees Regressor +2023-11-09 11:38:46,863:INFO:Total runtime is 0.09798425038655599 minutes +2023-11-09 11:38:46,866:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:46,867:INFO:Initializing create_model() +2023-11-09 11:38:46,867:INFO:create_model(self=, estimator=et, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:46,867:INFO:Checking exceptions +2023-11-09 11:38:46,867:INFO:Importing libraries +2023-11-09 11:38:46,867:INFO:Copying training dataset +2023-11-09 11:38:46,872:INFO:Defining folds +2023-11-09 11:38:46,872:INFO:Declaring metric variables +2023-11-09 11:38:46,875:INFO:Importing untrained model +2023-11-09 11:38:46,879:INFO:Extra Trees Regressor Imported successfully +2023-11-09 11:38:46,890:INFO:Starting cross validation +2023-11-09 11:38:46,891:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:47,250:INFO:Calculating mean and std +2023-11-09 11:38:47,251:INFO:Creating metrics dataframe +2023-11-09 11:38:47,255:INFO:Uploading results into container +2023-11-09 11:38:47,256:INFO:Uploading model into container now +2023-11-09 11:38:47,256:INFO:_master_model_container: 14 +2023-11-09 11:38:47,256:INFO:_display_container: 2 +2023-11-09 11:38:47,256:INFO:ExtraTreesRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:38:47,256:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:47,393:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:47,394:INFO:Creating metrics dataframe +2023-11-09 11:38:47,404:INFO:Initializing AdaBoost Regressor +2023-11-09 11:38:47,404:INFO:Total runtime is 0.1070099155108134 minutes +2023-11-09 11:38:47,408:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:47,408:INFO:Initializing create_model() +2023-11-09 11:38:47,409:INFO:create_model(self=, estimator=ada, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:47,409:INFO:Checking exceptions +2023-11-09 11:38:47,409:INFO:Importing libraries +2023-11-09 11:38:47,409:INFO:Copying training dataset +2023-11-09 11:38:47,412:INFO:Defining folds +2023-11-09 11:38:47,412:INFO:Declaring metric variables +2023-11-09 11:38:47,416:INFO:Importing untrained model +2023-11-09 11:38:47,419:INFO:AdaBoost Regressor Imported successfully +2023-11-09 11:38:47,425:INFO:Starting cross validation +2023-11-09 11:38:47,426:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:47,578:INFO:Calculating mean and std +2023-11-09 11:38:47,579:INFO:Creating metrics dataframe +2023-11-09 11:38:47,582:INFO:Uploading results into container +2023-11-09 11:38:47,583:INFO:Uploading model into container now +2023-11-09 11:38:47,583:INFO:_master_model_container: 15 +2023-11-09 11:38:47,583:INFO:_display_container: 2 +2023-11-09 11:38:47,583:INFO:AdaBoostRegressor(random_state=123) +2023-11-09 11:38:47,584:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:47,728:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:47,729:INFO:Creating metrics dataframe +2023-11-09 11:38:47,739:INFO:Initializing Gradient Boosting Regressor +2023-11-09 11:38:47,740:INFO:Total runtime is 0.11259630123774211 minutes +2023-11-09 11:38:47,743:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:47,743:INFO:Initializing create_model() +2023-11-09 11:38:47,744:INFO:create_model(self=, estimator=gbr, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:47,744:INFO:Checking exceptions +2023-11-09 11:38:47,744:INFO:Importing libraries +2023-11-09 11:38:47,744:INFO:Copying training dataset +2023-11-09 11:38:47,747:INFO:Defining folds +2023-11-09 11:38:47,747:INFO:Declaring metric variables +2023-11-09 11:38:47,751:INFO:Importing untrained model +2023-11-09 11:38:47,754:INFO:Gradient Boosting Regressor Imported successfully +2023-11-09 11:38:47,761:INFO:Starting cross validation +2023-11-09 11:38:47,762:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:47,920:INFO:Calculating mean and std +2023-11-09 11:38:47,921:INFO:Creating metrics dataframe +2023-11-09 11:38:47,925:INFO:Uploading results into container +2023-11-09 11:38:47,926:INFO:Uploading model into container now +2023-11-09 11:38:47,926:INFO:_master_model_container: 16 +2023-11-09 11:38:47,926:INFO:_display_container: 2 +2023-11-09 11:38:47,926:INFO:GradientBoostingRegressor(random_state=123) +2023-11-09 11:38:47,926:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:48,059:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:48,059:INFO:Creating metrics dataframe +2023-11-09 11:38:48,069:INFO:Initializing Light Gradient Boosting Machine +2023-11-09 11:38:48,070:INFO:Total runtime is 0.11809953848520915 minutes +2023-11-09 11:38:48,073:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:48,074:INFO:Initializing create_model() +2023-11-09 11:38:48,074:INFO:create_model(self=, estimator=lightgbm, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:48,074:INFO:Checking exceptions +2023-11-09 11:38:48,074:INFO:Importing libraries +2023-11-09 11:38:48,074:INFO:Copying training dataset +2023-11-09 11:38:48,078:INFO:Defining folds +2023-11-09 11:38:48,078:INFO:Declaring metric variables +2023-11-09 11:38:48,081:INFO:Importing untrained model +2023-11-09 11:38:48,086:INFO:Light Gradient Boosting Machine Imported successfully +2023-11-09 11:38:48,092:INFO:Starting cross validation +2023-11-09 11:38:48,092:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:48,700:INFO:Calculating mean and std +2023-11-09 11:38:48,701:INFO:Creating metrics dataframe +2023-11-09 11:38:48,704:INFO:Uploading results into container +2023-11-09 11:38:48,705:INFO:Uploading model into container now +2023-11-09 11:38:48,705:INFO:_master_model_container: 17 +2023-11-09 11:38:48,706:INFO:_display_container: 2 +2023-11-09 11:38:48,706:INFO:LGBMRegressor(n_jobs=-1, random_state=123) +2023-11-09 11:38:48,706:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:48,843:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:48,844:INFO:Creating metrics dataframe +2023-11-09 11:38:48,854:INFO:Initializing Dummy Regressor +2023-11-09 11:38:48,854:INFO:Total runtime is 0.13117225567499796 minutes +2023-11-09 11:38:48,858:INFO:SubProcess create_model() called ================================== +2023-11-09 11:38:48,858:INFO:Initializing create_model() +2023-11-09 11:38:48,858:INFO:create_model(self=, estimator=dummy, fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:48,858:INFO:Checking exceptions +2023-11-09 11:38:48,858:INFO:Importing libraries +2023-11-09 11:38:48,859:INFO:Copying training dataset +2023-11-09 11:38:48,862:INFO:Defining folds +2023-11-09 11:38:48,862:INFO:Declaring metric variables +2023-11-09 11:38:48,866:INFO:Importing untrained model +2023-11-09 11:38:48,869:INFO:Dummy Regressor Imported successfully +2023-11-09 11:38:48,874:INFO:Starting cross validation +2023-11-09 11:38:48,875:INFO:Cross validating with TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), n_jobs=-1 +2023-11-09 11:38:48,960:INFO:Calculating mean and std +2023-11-09 11:38:48,960:INFO:Creating metrics dataframe +2023-11-09 11:38:48,966:INFO:Uploading results into container +2023-11-09 11:38:48,967:INFO:Uploading model into container now +2023-11-09 11:38:48,971:INFO:_master_model_container: 18 +2023-11-09 11:38:48,971:INFO:_display_container: 2 +2023-11-09 11:38:48,971:INFO:DummyRegressor() +2023-11-09 11:38:48,971:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:49,112:INFO:SubProcess create_model() end ================================== +2023-11-09 11:38:49,112:INFO:Creating metrics dataframe +2023-11-09 11:38:49,133:INFO:Initializing create_model() +2023-11-09 11:38:49,133:INFO:create_model(self=, estimator=HuberRegressor(), fold=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=3, test_size=None), round=4, cross_validation=False, predict=False, fit_kwargs={}, groups=None, refit=True, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=None, model_only=True, return_train_score=False, kwargs={}) +2023-11-09 11:38:49,133:INFO:Checking exceptions +2023-11-09 11:38:49,135:INFO:Importing libraries +2023-11-09 11:38:49,135:INFO:Copying training dataset +2023-11-09 11:38:49,137:INFO:Defining folds +2023-11-09 11:38:49,138:INFO:Declaring metric variables +2023-11-09 11:38:49,138:INFO:Importing untrained model +2023-11-09 11:38:49,138:INFO:Declaring custom model +2023-11-09 11:38:49,138:INFO:Huber Regressor Imported successfully +2023-11-09 11:38:49,139:INFO:Cross validation set to False +2023-11-09 11:38:49,139:INFO:Fitting Model +2023-11-09 11:38:49,162:INFO:HuberRegressor() +2023-11-09 11:38:49,163:INFO:create_model() successfully completed...................................... +2023-11-09 11:38:49,321:INFO:_master_model_container: 18 +2023-11-09 11:38:49,321:INFO:_display_container: 2 +2023-11-09 11:38:49,322:INFO:HuberRegressor() +2023-11-09 11:38:49,322:INFO:compare_models() successfully completed...................................... +2023-11-09 11:38:57,138:INFO:Initializing predict_model() +2023-11-09 11:38:57,139:INFO:predict_model(self=, estimator=HuberRegressor(), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=.encode_labels at 0x7fbb2cbab1f0>) +2023-11-09 11:38:57,139:INFO:Checking exceptions +2023-11-09 11:38:57,139:INFO:Preloading libraries +2023-11-09 11:38:57,141:INFO:Set up data. +2023-11-09 11:38:57,144:INFO:Set up index. +2023-11-09 11:44:30,005:INFO:Initializing predict_model() +2023-11-09 11:44:30,006:INFO:predict_model(self=, estimator=HuberRegressor(), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=.encode_labels at 0x7fbb2d060940>) +2023-11-09 11:44:30,006:INFO:Checking exceptions +2023-11-09 11:44:30,006:INFO:Preloading libraries +2023-11-09 11:44:30,008:INFO:Set up data. +2023-11-09 11:44:30,011:INFO:Set up index. +2023-11-09 11:45:14,453:INFO:Initializing predict_model() +2023-11-09 11:45:14,454:INFO:predict_model(self=, estimator=HuberRegressor(), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=.encode_labels at 0x7fbb44e77550>) +2023-11-09 11:45:14,454:INFO:Checking exceptions +2023-11-09 11:45:14,454:INFO:Preloading libraries +2023-11-09 11:45:14,456:INFO:Set up data. +2023-11-09 11:45:14,458:INFO:Set up index.