From d37503e4c9343b156084c0ef7ba3a2354b2ca948 Mon Sep 17 00:00:00 2001 From: Vincent Jacques Date: Tue, 24 Oct 2023 12:12:26 +0000 Subject: [PATCH] Publish version 0.10.2 --- doc-sources/changelog.rst | 12 +++++------- doc-sources/conceptual-overview.rst | 2 +- doc-sources/get-started.rst | 8 ++++---- doc-sources/user-guide.rst | 6 +++--- docs/.buildinfo | 2 +- docs/.doctrees/changelog.doctree | Bin 39485 -> 40191 bytes docs/.doctrees/conceptual-overview.doctree | Bin 108517 -> 108495 bytes docs/.doctrees/environment.pickle | Bin 79259 -> 78842 bytes docs/.doctrees/get-started.doctree | Bin 50476 -> 50410 bytes docs/.doctrees/reference.doctree | Bin 164980 -> 164804 bytes docs/.doctrees/user-guide.doctree | Bin 114496 -> 114419 bytes docs/_sources/changelog.rst.txt | 12 +++++------- docs/_sources/conceptual-overview.rst.txt | 4 ++-- docs/_sources/get-started.rst.txt | 14 +++++++------- docs/_sources/user-guide.rst.txt | 12 ++++++------ docs/_static/documentation_options.js | 2 +- docs/changelog.html | 20 ++++++++------------ docs/conceptual-overview.html | 4 ++-- docs/contributor-guide.html | 4 ++-- docs/genindex.html | 14 +++++++------- docs/get-started.html | 18 +++++++++--------- docs/index.html | 4 ++-- docs/objects.inv | Bin 1632 -> 1628 bytes docs/reference.html | 12 ++++++------ docs/search.html | 4 ++-- docs/searchindex.js | 2 +- docs/user-guide.html | 8 ++++---- lincs/__init__.py | 2 +- 28 files changed, 79 insertions(+), 87 deletions(-) diff --git a/doc-sources/changelog.rst b/doc-sources/changelog.rst index 4452fe5d..3f1de12d 100644 --- a/doc-sources/changelog.rst +++ b/doc-sources/changelog.rst @@ -4,18 +4,16 @@ Changelog ========= -Version 0.10.1 -============== - -- Fix ``lincs visualize`` to use criteria's min/max values and category correlation - -Version 0.10.0 -============== +Versions 0.10.0 to 0.10.2 +========================= This is the first release candidate for version 1.0.0. - **Breaking**: Allow more flexible description of accepted values in the model json schema. See user guide for details. - **Breaking**: Rename option ``--ucncs.approach`` to ``--ucncs.strategy`` +- **Breaking**: Rename option ``--output-classified-alternatives`` to ``--output-alternatives`` +- Fix line ends on Windows +- Fix ``lincs visualize`` to use criteria's min/max values and category correlation - Validate consistency with problem when loading alternatives or model files - Output "reproduction command" in ``lincs classify`` - Improve documentation diff --git a/doc-sources/conceptual-overview.rst b/doc-sources/conceptual-overview.rst index 1cb3d034..9a02682e 100644 --- a/doc-sources/conceptual-overview.rst +++ b/doc-sources/conceptual-overview.rst @@ -362,7 +362,7 @@ If yes, they get a partial scholarship. .. STOP .. START concept-example/expected-classified-alternatives.csv - # Reproduction command (with lincs version 0.10.2-dev): lincs classify problem.yml model.yml alternatives.csv + # Reproduction command (with lincs version 0.10.2): lincs classify problem.yml model.yml alternatives.csv name,Math,Physics,Literature,History,category A,1,1,1,1,"Full scholarship" B,1,1,1,0,"Full scholarship" diff --git a/doc-sources/get-started.rst b/doc-sources/get-started.rst index 9cac2d08..e738b887 100644 --- a/doc-sources/get-started.rst +++ b/doc-sources/get-started.rst @@ -86,7 +86,7 @@ So, start by generating a classification problem with 4 criteria and 3 categorie The generated ``problem.yml`` should look like:: - # Reproduction command (with lincs version 0.10.2-dev): lincs generate classification-problem 4 3 --random-seed 40 + # Reproduction command (with lincs version 0.10.2): lincs generate classification-problem 4 3 --random-seed 40 kind: classification-problem format_version: 1 criteria: @@ -142,7 +142,7 @@ Then generate an NCS classification model:: It should look like:: - # Reproduction command (with lincs version 0.10.2-dev): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort + # Reproduction command (with lincs version 0.10.2): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort kind: ncs-classification-model format_version: 1 accepted_values: @@ -212,7 +212,7 @@ Then we'll need to think about the how the ``--max-imbalance`` option interacts It should start with something like this, and contain 1000 alternatives:: - # Reproduction command (with lincs version 0.10.2-dev): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0 + # Reproduction command (with lincs version 0.10.2): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0 name,"Criterion 1","Criterion 2","Criterion 3","Criterion 4",category "Alternative 1",0.37454012,0.796543002,0.95071429,0.183434784,"Category 3" "Alternative 2",0.731993914,0.779690981,0.598658502,0.596850157,"Category 2" @@ -268,7 +268,7 @@ The learning set doesn't contain all the information from the original model, and the trained model was reconstituted from this partial information, so it is numerically different:: - # Reproduction command (with lincs version 0.10.2-dev): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver glop --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0 + # Reproduction command (with lincs version 0.10.2): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver glop --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0 # Termination condition: target accuracy reached # Number of iterations: 22 kind: ncs-classification-model diff --git a/doc-sources/user-guide.rst b/doc-sources/user-guide.rst index af27a74f..cf7ce4e9 100644 --- a/doc-sources/user-guide.rst +++ b/doc-sources/user-guide.rst @@ -475,7 +475,7 @@ Here is an example using the `Alglib `_ solver:: It should produce a very similar model, with slight numerical differences. .. START alglib-learning/expected-alglib-trained-model.yml - # Reproduction command (with lincs version 0.10.2-dev): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver alglib --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0 + # Reproduction command (with lincs version 0.10.2): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver alglib --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0 # Termination condition: target accuracy reached # Number of iterations: 9 kind: ncs-classification-model @@ -591,7 +591,7 @@ And:: They should produce a different kind of model, with the sufficient coalitions specified explicitly by their roots:: - # Reproduction command (with lincs version 0.10.2-dev): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions + # Reproduction command (with lincs version 0.10.2): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions kind: ncs-classification-model format_version: 1 accepted_values: @@ -613,7 +613,7 @@ They should produce a different kind of model, with the sufficient coalitions sp .. STOP .. START sat-learnings/expected-max-sat-by-separation-trained-model.yml - # Reproduction command (with lincs version 0.10.2-dev): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy max-sat-by-separation + # Reproduction command (with lincs version 0.10.2): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy max-sat-by-separation kind: ncs-classification-model format_version: 1 accepted_values: diff --git a/docs/.buildinfo b/docs/.buildinfo index c0af87c1..f10fbebc 100644 --- a/docs/.buildinfo +++ b/docs/.buildinfo @@ -1,4 +1,4 @@ # Sphinx build info version 1 # This file hashes the configuration used when building these files. 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b/docs/_sources/changelog.rst.txt @@ -4,18 +4,16 @@ Changelog ========= -Version 0.10.1 -============== - -- Fix ``lincs visualize`` to use criteria's min/max values and category correlation - -Version 0.10.0 -============== +Versions 0.10.0 to 0.10.2 +========================= This is the first release candidate for version 1.0.0. - **Breaking**: Allow more flexible description of accepted values in the model json schema. See user guide for details. - **Breaking**: Rename option ``--ucncs.approach`` to ``--ucncs.strategy`` +- **Breaking**: Rename option ``--output-classified-alternatives`` to ``--output-alternatives`` +- Fix line ends on Windows +- Fix ``lincs visualize`` to use criteria's min/max values and category correlation - Validate consistency with problem when loading alternatives or model files - Output "reproduction command" in ``lincs classify`` - Improve documentation diff --git a/docs/_sources/conceptual-overview.rst.txt b/docs/_sources/conceptual-overview.rst.txt index 5635a5bc..9a02682e 100644 --- a/docs/_sources/conceptual-overview.rst.txt +++ b/docs/_sources/conceptual-overview.rst.txt @@ -160,7 +160,7 @@ The profiles for this model look like this: lincs visualize classification-model problem.yml model.yml concept-example-model.png cp concept-example-model.png ../../../../doc-sources - lincs classify problem.yml model.yml alternatives.csv --output-classified-alternatives classified-alternatives.csv + lincs classify problem.yml model.yml alternatives.csv --output-alternatives classified-alternatives.csv diff classified-alternatives.csv expected-classified-alternatives.csv .. STOP @@ -362,7 +362,7 @@ If yes, they get a partial scholarship. .. STOP .. START concept-example/expected-classified-alternatives.csv - # Reproduction command (with lincs version 0.10.1): lincs classify problem.yml model.yml alternatives.csv + # Reproduction command (with lincs version 0.10.2): lincs classify problem.yml model.yml alternatives.csv name,Math,Physics,Literature,History,category A,1,1,1,1,"Full scholarship" B,1,1,1,0,"Full scholarship" diff --git a/docs/_sources/get-started.rst.txt b/docs/_sources/get-started.rst.txt index 4c14f103..e738b887 100644 --- a/docs/_sources/get-started.rst.txt +++ b/docs/_sources/get-started.rst.txt @@ -86,7 +86,7 @@ So, start by generating a classification problem with 4 criteria and 3 categorie The generated ``problem.yml`` should look like:: - # Reproduction command (with lincs version 0.10.1): lincs generate classification-problem 4 3 --random-seed 40 + # Reproduction command (with lincs version 0.10.2): lincs generate classification-problem 4 3 --random-seed 40 kind: classification-problem format_version: 1 criteria: @@ -142,7 +142,7 @@ Then generate an NCS classification model:: It should look like:: - # Reproduction command (with lincs version 0.10.1): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort + # Reproduction command (with lincs version 0.10.2): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort kind: ncs-classification-model format_version: 1 accepted_values: @@ -195,7 +195,7 @@ It should output something like: And finally generate a set of classified alternatives:: - lincs generate classified-alternatives problem.yml model.yml 1000 --output-classified-alternatives learning-set.csv + lincs generate classified-alternatives problem.yml model.yml 1000 --output-alternatives learning-set.csv .. APPEND-TO-LAST-LINE --random-seed 42 .. STOP @@ -212,7 +212,7 @@ Then we'll need to think about the how the ``--max-imbalance`` option interacts It should start with something like this, and contain 1000 alternatives:: - # Reproduction command (with lincs version 0.10.1): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0 + # Reproduction command (with lincs version 0.10.2): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0 name,"Criterion 1","Criterion 2","Criterion 3","Criterion 4",category "Alternative 1",0.37454012,0.796543002,0.95071429,0.183434784,"Category 3" "Alternative 2",0.731993914,0.779690981,0.598658502,0.596850157,"Category 2" @@ -268,7 +268,7 @@ The learning set doesn't contain all the information from the original model, and the trained model was reconstituted from this partial information, so it is numerically different:: - # Reproduction command (with lincs version 0.10.1): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver glop --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0 + # Reproduction command (with lincs version 0.10.2): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver glop --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0 # Termination condition: target accuracy reached # Number of iterations: 22 kind: ncs-classification-model @@ -303,7 +303,7 @@ To see how close a trained model is to the original one, you can reclassify a te First, generate a testing set:: - lincs generate classified-alternatives problem.yml model.yml 10000 --output-classified-alternatives testing-set.csv + lincs generate classified-alternatives problem.yml model.yml 10000 --output-alternatives testing-set.csv .. APPEND-TO-LAST-LINE --random-seed 44 .. STOP @@ -314,7 +314,7 @@ First, generate a testing set:: And ask the trained model to classify it:: - lincs classify problem.yml trained-model.yml testing-set.csv --output-classified-alternatives reclassified-testing-set.csv + lincs classify problem.yml trained-model.yml testing-set.csv --output-alternatives reclassified-testing-set.csv .. STOP diff --git a/docs/_sources/user-guide.rst.txt b/docs/_sources/user-guide.rst.txt index 004413f5..cf7ce4e9 100644 --- a/docs/_sources/user-guide.rst.txt +++ b/docs/_sources/user-guide.rst.txt @@ -33,7 +33,7 @@ To describe problems, *lincs* uses YAML files conforming to the `JSON schema /dev/null - lincs classify problem.yml mrsort-model.yml unclassified-alternatives.csv --output-classified-alternatives classified-alternatives.csv + lincs classify problem.yml mrsort-model.yml unclassified-alternatives.csv --output-alternatives classified-alternatives.csv diff <(tail -n +2 classified-alternatives.csv) expected-classified-alternatives.csv .. STOP @@ -336,7 +336,7 @@ With its default settings, ``lincs generate classified-alternatives`` requires o lincs generate classified-alternatives problem.yml model.yml 100 -.. APPEND-TO-LAST-LINE --output-classified-alternatives learning-set.csv +.. APPEND-TO-LAST-LINE --output-alternatives learning-set.csv .. STOP This generates 100 random alternatives, and then classifies them according to the model. @@ -475,7 +475,7 @@ Here is an example using the `Alglib `_ solver:: It should produce a very similar model, with slight numerical differences. .. START alglib-learning/expected-alglib-trained-model.yml - # Reproduction command (with lincs version 0.10.1): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver alglib --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0 + # Reproduction command (with lincs version 0.10.2): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver alglib --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0 # Termination condition: target accuracy reached # Number of iterations: 9 kind: ncs-classification-model @@ -591,7 +591,7 @@ And:: They should produce a different kind of model, with the sufficient coalitions specified explicitly by their roots:: - # Reproduction command (with lincs version 0.10.1): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions + # Reproduction command (with lincs version 0.10.2): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions kind: ncs-classification-model format_version: 1 accepted_values: @@ -613,7 +613,7 @@ They should produce a different kind of model, with the sufficient coalitions sp .. STOP .. START sat-learnings/expected-max-sat-by-separation-trained-model.yml - # Reproduction command (with lincs version 0.10.1): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy max-sat-by-separation + # Reproduction command (with lincs version 0.10.2): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy max-sat-by-separation kind: ncs-classification-model format_version: 1 accepted_values: @@ -646,7 +646,7 @@ you can use it to classify alternatives with ``lincs classify problem.yml model. The ``category`` column in the input alternatives file is ignored and may be empty. Note that the input files will not be modified: the classified alternatives will be printed on the standard output -or written in the file specified by ``--output-classified-alternatives``. +or written in the file specified by ``--output-alternatives``. Computing a classification accuracy ----------------------------------- diff --git a/docs/_static/documentation_options.js b/docs/_static/documentation_options.js index 1a724067..db6d22fe 100644 --- a/docs/_static/documentation_options.js +++ b/docs/_static/documentation_options.js @@ -1,6 +1,6 @@ var DOCUMENTATION_OPTIONS = { URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'), - VERSION: '0.10.1', + VERSION: '0.10.2', LANGUAGE: 'en', COLLAPSE_INDEX: false, BUILDER: 'html', diff --git a/docs/changelog.html b/docs/changelog.html index 90388610..013fbe13 100644 --- a/docs/changelog.html +++ b/docs/changelog.html @@ -5,11 +5,11 @@ - Changelog — lincs 0.10.1 documentation + Changelog — lincs 0.10.2 documentation - + @@ -34,18 +34,15 @@

Changelog

-
-

Version 0.10.1

-
    -

  • Fix lincs visualize to use criteria’s min/max values and category correlation

    • -
-
-
-

Version 0.10.0

+
+

Versions 0.10.0 to 0.10.2

This is the first release candidate for version 1.0.0.

  • Breaking: Allow more flexible description of accepted values in the model json schema. See user guide for details.

  • Breaking: Rename option --ucncs.approach to --ucncs.strategy

    • +

  • Breaking: Rename option --output-classified-alternatives to --output-alternatives

    • +

  • Fix line ends on Windows

    • +

  • Fix lincs visualize to use criteria’s min/max values and category correlation

  • Validate consistency with problem when loading alternatives or model files

  • Output “reproduction command” in lincs classify

  • Improve documentation

    • @@ -271,8 +268,7 @@

    Navigation

  • Reference
  • Contributor guide
  • Changelog
      -
    • Version 0.10.1
      • -
    • Version 0.10.0
      • +
    • Versions 0.10.0 to 0.10.2
    • Versions 0.9.0 to 0.9.2
    • Version 0.8.7
    • Versions 0.8.5 to 0.8.6
      • diff --git a/docs/conceptual-overview.html b/docs/conceptual-overview.html index 0dc0cb4d..f96868ba 100644 --- a/docs/conceptual-overview.html +++ b/docs/conceptual-overview.html @@ -5,11 +5,11 @@ - Conceptual overview — lincs 0.10.1 documentation + Conceptual overview — lincs 0.10.2 documentation - + diff --git a/docs/contributor-guide.html b/docs/contributor-guide.html index 81d02b04..50d16a72 100644 --- a/docs/contributor-guide.html +++ b/docs/contributor-guide.html @@ -5,11 +5,11 @@ - Contributor guide — lincs 0.10.1 documentation + Contributor guide — lincs 0.10.2 documentation - + diff --git a/docs/genindex.html b/docs/genindex.html index e38be5f7..ca726bc3 100644 --- a/docs/genindex.html +++ b/docs/genindex.html @@ -4,11 +4,11 @@ - Index — lincs 0.10.1 documentation + Index — lincs 0.10.2 documentation - + @@ -240,12 +240,12 @@

      Symbols

  • - --output-classified-alternatives + --output-alternatives
  • @@ -454,7 +454,7 @@

    L

    lincs-classify command line option
      -
    • --output-classified-alternatives +
    • --output-alternatives
    • ALTERNATIVES
      • @@ -503,7 +503,7 @@

      L

    • --misclassified-count
      • -
    • --output-classified-alternatives +
    • --output-alternatives
    • --random-seed
      • diff --git a/docs/get-started.html b/docs/get-started.html index d6c6767c..e6d08e8a 100644 --- a/docs/get-started.html +++ b/docs/get-started.html @@ -5,11 +5,11 @@ - Get started — lincs 0.10.1 documentation + Get started — lincs 0.10.2 documentation - + @@ -73,7 +73,7 @@

      Get lincsproblem.yml should look like:

      -
      # Reproduction command (with lincs version 0.10.1): lincs generate classification-problem 4 3 --random-seed 40
+
      # Reproduction command (with lincs version 0.10.2): lincs generate classification-problem 4 3 --random-seed 40
 kind: classification-problem
 format_version: 1
 criteria:
@@ -111,7 +111,7 @@ 
      Get lincs
      # Reproduction command (with lincs version 0.10.1): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort
+
      # Reproduction command (with lincs version 0.10.2): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort
 kind: ncs-classification-model
 format_version: 1
 accepted_values:
@@ -140,7 +140,7 @@ 
      Get lincs
 
      And finally generate a set of classified alternatives:
      
-
      lincs generate classified-alternatives problem.yml model.yml 1000 --output-classified-alternatives learning-set.csv
+
      lincs generate classified-alternatives problem.yml model.yml 1000 --output-alternatives learning-set.csv
 
      
 
      
 
      The file format is documented in our reference documentation.
      
@@ -148,7 +148,7 @@ 
      Get lincs--max-imbalance option interacts with that feature.
      
 
      It should start with something like this, and contain 1000 alternatives:
      
-
      # Reproduction command (with lincs version 0.10.1): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0
+
      # Reproduction command (with lincs version 0.10.2): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0
 name,"Criterion 1","Criterion 2","Criterion 3","Criterion 4",category
 "Alternative 1",0.37454012,0.796543002,0.95071429,0.183434784,"Category 3"
 "Alternative 2",0.731993914,0.779690981,0.598658502,0.596850157,"Category 2"
@@ -172,7 +172,7 @@ 
      Get lincs
      # Reproduction command (with lincs version 0.10.1): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver glop --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0
+
      # Reproduction command (with lincs version 0.10.2): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver glop --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0
 # Termination condition: target accuracy reached
 # Number of iterations: 22
 kind: ncs-classification-model
@@ -196,11 +196,11 @@ 
      Get lincs
      lincs generate classified-alternatives problem.yml model.yml 10000 --output-classified-alternatives testing-set.csv
+
      lincs generate classified-alternatives problem.yml model.yml 10000 --output-alternatives testing-set.csv
 
      
 
      
 
      And ask the trained model to classify it:
      
-
      lincs classify problem.yml trained-model.yml testing-set.csv --output-classified-alternatives reclassified-testing-set.csv
+
      lincs classify problem.yml trained-model.yml testing-set.csv --output-alternatives reclassified-testing-set.csv
 
      
 
      
 
      There are a few differences between the original testing set and the reclassified one:
      
diff --git a/docs/index.html b/docs/index.html
index 7ef88464..752408b7 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -5,11 +5,11 @@
     
     
 
-    README — lincs 0.10.1 documentation
+    README — lincs 0.10.2 documentation
     
     
     
-    
+    
     
     
     
diff --git a/docs/objects.inv b/docs/objects.inv
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diff --git a/docs/reference.html b/docs/reference.html
index 0f792655..f0b074b5 100644
--- a/docs/reference.html
+++ b/docs/reference.html
@@ -5,11 +5,11 @@
     
     
 
-    Reference — lincs 0.10.1 documentation
+    Reference — lincs 0.10.2 documentation
     
     
     
-    
+    
     
     
     
@@ -416,8 +416,8 @@ 
      classifyOptions
      
 
      
-
      
---output-classified-alternatives <output_classified_alternatives>
      
+
      
+--output-alternatives <output_alternatives>
      
 
      Write classified alternatives to this file instead of standard output.
      
 
      
 
@@ -559,8 +559,8 @@ 
      classified-alternativesOptions
      
 
      
-
      
---output-classified-alternatives <output_classified_alternatives>
      
+
      
+--output-alternatives <output_alternatives>
      
 
      Write generated classified alternatives to this file instead of standard output.
      
 
      
 
diff --git a/docs/search.html b/docs/search.html
index 5727ee50..0c848211 100644
--- a/docs/search.html
+++ b/docs/search.html
@@ -4,12 +4,12 @@
   
     
     
-    Search — lincs 0.10.1 documentation
+    Search — lincs 0.10.2 documentation
     
     
     
     
-    
+    
     
     
     
diff --git a/docs/searchindex.js b/docs/searchindex.js
index c41b4ac8..779775fc 100644
--- a/docs/searchindex.js
+++ b/docs/searchindex.js
@@ -1 +1 @@
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\ No newline at end of file
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"cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.max-iterations-without-progress"]], "--mrsort.weights-profiles-breed.models-count": [[5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.models-count"]], "--mrsort.weights-profiles-breed.profiles-strategy": [[5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.profiles-strategy"]], "--mrsort.weights-profiles-breed.reinitialize-least-accurate.portion": [[5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.reinitialize-least-accurate.portion"]], "--mrsort.weights-profiles-breed.target-accuracy": [[5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.target-accuracy"]], "--mrsort.weights-profiles-breed.verbose": [[5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.verbose"]], "--mrsort.weights-profiles-breed.weights-strategy": [[5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.weights-strategy"]], "--output-alternatives": [[5, "cmdoption-lincs-classify-output-alternatives"], [5, "cmdoption-lincs-generate-classified-alternatives-output-alternatives"]], "--output-model": [[5, "cmdoption-lincs-generate-classification-model-output-model"], [5, "cmdoption-lincs-learn-classification-model-output-model"]], "--output-problem": [[5, "cmdoption-lincs-generate-classification-problem-output-problem"]], "--quiet": [[5, "cmdoption-lincs-info-has-gpu-quiet"]], "--random-seed": [[5, "cmdoption-lincs-generate-classification-model-random-seed"], [5, "cmdoption-lincs-generate-classification-problem-random-seed"], [5, "cmdoption-lincs-generate-classified-alternatives-random-seed"]], "--ucncs.strategy": [[5, "cmdoption-lincs-learn-classification-model-ucncs.strategy"]], "--version": [[5, "cmdoption-lincs-version"]], "alternatives": [[5, "cmdoption-lincs-classify-arg-ALTERNATIVES"]], "alternatives_count": [[5, "cmdoption-lincs-generate-classified-alternatives-arg-ALTERNATIVES_COUNT"]], "categories_count": [[5, "cmdoption-lincs-generate-classification-problem-arg-CATEGORIES_COUNT"]], "criteria_count": [[5, "cmdoption-lincs-generate-classification-problem-arg-CRITERIA_COUNT"]], "learning_set": [[5, "cmdoption-lincs-learn-classification-model-arg-LEARNING_SET"]], "model": [[5, "cmdoption-lincs-classification-accuracy-arg-MODEL"], [5, "cmdoption-lincs-classify-arg-MODEL"], [5, "cmdoption-lincs-generate-classified-alternatives-arg-MODEL"], [5, "cmdoption-lincs-visualize-classification-model-arg-MODEL"]], "output": [[5, "cmdoption-lincs-visualize-classification-model-arg-OUTPUT"]], "problem": [[5, "cmdoption-lincs-classification-accuracy-arg-PROBLEM"], [5, "cmdoption-lincs-classify-arg-PROBLEM"], [5, "cmdoption-lincs-generate-classification-model-arg-PROBLEM"], [5, "cmdoption-lincs-generate-classified-alternatives-arg-PROBLEM"], [5, "cmdoption-lincs-learn-classification-model-arg-PROBLEM"], [5, "cmdoption-lincs-visualize-classification-model-arg-PROBLEM"]], "testing_set": [[5, "cmdoption-lincs-classification-accuracy-arg-TESTING_SET"]], "lincs command line option": [[5, "cmdoption-lincs-version"]], "lincs-classification-accuracy command line option": [[5, "cmdoption-lincs-classification-accuracy-arg-MODEL"], [5, "cmdoption-lincs-classification-accuracy-arg-PROBLEM"], [5, "cmdoption-lincs-classification-accuracy-arg-TESTING_SET"]], "lincs-classify command line option": [[5, "cmdoption-lincs-classify-arg-ALTERNATIVES"], [5, "cmdoption-lincs-classify-arg-MODEL"], [5, "cmdoption-lincs-classify-arg-PROBLEM"], [5, "cmdoption-lincs-classify-output-alternatives"]], "lincs-generate-classification-model command line option": [[5, "cmdoption-lincs-generate-classification-model-arg-PROBLEM"], [5, "cmdoption-lincs-generate-classification-model-model-type"], [5, "cmdoption-lincs-generate-classification-model-mrsort.fixed-weights-sum"], [5, "cmdoption-lincs-generate-classification-model-output-model"], [5, "cmdoption-lincs-generate-classification-model-random-seed"]], "lincs-generate-classification-problem command line option": [[5, "cmdoption-lincs-generate-classification-problem-allow-decreasing-criteria"], [5, "cmdoption-lincs-generate-classification-problem-arg-CATEGORIES_COUNT"], [5, "cmdoption-lincs-generate-classification-problem-arg-CRITERIA_COUNT"], [5, "cmdoption-lincs-generate-classification-problem-denormalized-min-max"], [5, "cmdoption-lincs-generate-classification-problem-output-problem"], [5, "cmdoption-lincs-generate-classification-problem-random-seed"]], "lincs-generate-classified-alternatives command line option": [[5, "cmdoption-lincs-generate-classified-alternatives-arg-ALTERNATIVES_COUNT"], [5, "cmdoption-lincs-generate-classified-alternatives-arg-MODEL"], [5, "cmdoption-lincs-generate-classified-alternatives-arg-PROBLEM"], [5, "cmdoption-lincs-generate-classified-alternatives-max-imbalance"], [5, "cmdoption-lincs-generate-classified-alternatives-misclassified-count"], [5, "cmdoption-lincs-generate-classified-alternatives-output-alternatives"], [5, "cmdoption-lincs-generate-classified-alternatives-random-seed"]], "lincs-info-has-gpu command line option": [[5, "cmdoption-lincs-info-has-gpu-quiet"]], "lincs-learn-classification-model command line option": [[5, "cmdoption-lincs-learn-classification-model-arg-LEARNING_SET"], [5, "cmdoption-lincs-learn-classification-model-arg-PROBLEM"], [5, "cmdoption-lincs-learn-classification-model-model-type"], [5, "cmdoption-lincs-learn-classification-model-mrsort.strategy"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.accuracy-heuristic.processor"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.accuracy-heuristic.random-seed"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.breed-strategy"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.initialization-strategy"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.linear-program.solver"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.max-duration"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.max-duration-without-progress"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.max-iterations"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.max-iterations-without-progress"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.models-count"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.profiles-strategy"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.reinitialize-least-accurate.portion"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.target-accuracy"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.verbose"], [5, "cmdoption-lincs-learn-classification-model-mrsort.weights-profiles-breed.weights-strategy"], [5, "cmdoption-lincs-learn-classification-model-output-model"], [5, "cmdoption-lincs-learn-classification-model-ucncs.strategy"]], "lincs-visualize-classification-model command line option": [[5, "cmdoption-lincs-visualize-classification-model-alternatives"], [5, "cmdoption-lincs-visualize-classification-model-alternatives-count"], [5, "cmdoption-lincs-visualize-classification-model-arg-MODEL"], [5, "cmdoption-lincs-visualize-classification-model-arg-OUTPUT"], [5, "cmdoption-lincs-visualize-classification-model-arg-PROBLEM"]]}})
\ No newline at end of file
diff --git a/docs/user-guide.html b/docs/user-guide.html
index 189f2ec4..e959ec80 100644
--- a/docs/user-guide.html
+++ b/docs/user-guide.html
@@ -5,11 +5,11 @@
     
     
 
-    User Guide — lincs 0.10.1 documentation
+    User Guide — lincs 0.10.2 documentation
     
     
     
-    
+    
     
     
     
@@ -420,7 +420,7 @@ 
      SAT-based strategies
      
 
      
 
      They should produce a different kind of model, with the sufficient coalitions specified explicitly by their roots:
      
-
      # Reproduction command (with lincs version 0.10.1): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions
+
      # Reproduction command (with lincs version 0.10.2): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions
 kind: ncs-classification-model
 format_version: 1
 accepted_values:
@@ -451,7 +451,7 @@ 
      Classifying alternativeslincs classify problem.yml model.yml alternatives.csv.
      
 
      The category column in the input alternatives file is ignored and may be empty.
      
 
      Note that the input files will not be modified: the classified alternatives will be printed on the standard output
-or written in the file specified by --output-classified-alternatives.
      
+or written in the file specified by --output-alternatives.

Computing a classification accuracy

diff --git a/lincs/__init__.py b/lincs/__init__.py index 248985bf..02fc8575 100644 --- a/lincs/__init__.py +++ b/lincs/__init__.py @@ -1,6 +1,6 @@ # Copyright 2023 Vincent Jacques -__version__ = "0.10.2-dev" +__version__ = "0.10.2" # I/O from liblincs import DataValidationException