diff --git a/doc-sources/conceptual-overview/conceptual-overview.ipynb b/doc-sources/conceptual-overview/conceptual-overview.ipynb index b98db066..db044e2d 100644 --- a/doc-sources/conceptual-overview/conceptual-overview.ipynb +++ b/doc-sources/conceptual-overview/conceptual-overview.ipynb @@ -21,7 +21,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): lincs classify problem.yml model.yml alternatives.csv\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs classify problem.yml model.yml alternatives.csv\n", "name,Math,Physics,Literature,History,category\n", "A,1,1,1,1,\"Full scholarship\"\n", "B,1,1,1,0,\"Full scholarship\"\n", diff --git a/doc-sources/get-started.rst b/doc-sources/get-started.rst index 72363775..9e94308b 100644 --- a/doc-sources/get-started.rst +++ b/doc-sources/get-started.rst @@ -68,7 +68,7 @@ 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 0.11.0): lincs generate classification-problem 4 3 --random-seed 40 + # Reproduction command (with lincs version 0.11.1-dev): lincs generate classification-problem 4 3 --random-seed 40 kind: classification-problem format_version: 1 criteria: @@ -132,7 +132,7 @@ Then generate an NCS classification model:: It should look like:: - # Reproduction command (with lincs version 0.11.0): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort + # Reproduction command (with lincs version 0.11.1-dev): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort kind: ncs-classification-model format_version: 1 accepted_values: @@ -199,7 +199,7 @@ 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 0.11.0): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0 + # Reproduction command (with lincs version 0.11.1-dev): 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,"Best category" "Alternative 2",0.731993914,0.779690981,0.598658502,0.596850157,"Intermediate category 1" @@ -237,7 +237,7 @@ 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 0.11.0): 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 0.11.1-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 kind: ncs-classification-model format_version: 1 accepted_values: diff --git a/doc-sources/get-started/get-started.ipynb b/doc-sources/get-started/get-started.ipynb index 14cf5b6c..3c00b079 100644 --- a/doc-sources/get-started/get-started.ipynb +++ b/doc-sources/get-started/get-started.ipynb @@ -48,7 +48,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): lincs generate classification-problem 4 3 --random-seed 40\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs generate classification-problem 4 3 --random-seed 40\n", "kind: classification-problem\n", "format_version: 1\n", "criteria:\n", @@ -126,7 +126,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort\n", "kind: ncs-classification-model\n", "format_version: 1\n", "accepted_values:\n", @@ -216,7 +216,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0\n", "name,\"Criterion 1\",\"Criterion 2\",\"Criterion 3\",\"Criterion 4\",category\n", "\"Alternative 1\",0.37454012,0.796543002,0.95071429,0.183434784,\"Best category\"\n", "\"Alternative 2\",0.731993914,0.779690981,0.598658502,0.596850157,\"Intermediate category 1\"\n", @@ -270,7 +270,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): 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\n", + "# Reproduction command (with lincs version 0.11.1-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\n", "kind: ncs-classification-model\n", "format_version: 1\n", "accepted_values:\n", diff --git a/doc-sources/user-guide.rst b/doc-sources/user-guide.rst index ffa6adcc..344ae835 100644 --- a/doc-sources/user-guide.rst +++ b/doc-sources/user-guide.rst @@ -473,7 +473,7 @@ And:: They produce a different kind of model, with the sufficient coalitions specified explicitly by their roots:: - # Reproduction command (with lincs version 0.11.0): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions + # Reproduction command (with lincs version 0.11.1-dev): 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: diff --git a/doc-sources/user-guide/alglib-learning/alglib-learning.ipynb b/doc-sources/user-guide/alglib-learning/alglib-learning.ipynb index ec946a2c..6dcabf4d 100644 --- a/doc-sources/user-guide/alglib-learning/alglib-learning.ipynb +++ b/doc-sources/user-guide/alglib-learning/alglib-learning.ipynb @@ -27,7 +27,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): 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\n", + "# Reproduction command (with lincs version 0.11.1-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\n", "kind: ncs-classification-model\n", "format_version: 1\n", "accepted_values:\n", diff --git a/doc-sources/user-guide/gpu-learning/gpu-learning.ipynb b/doc-sources/user-guide/gpu-learning/gpu-learning.ipynb index 29646dcd..827dc134 100644 --- a/doc-sources/user-guide/gpu-learning/gpu-learning.ipynb +++ b/doc-sources/user-guide/gpu-learning/gpu-learning.ipynb @@ -27,7 +27,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): 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 gpu --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\n", + "# Reproduction command (with lincs version 0.11.1-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 gpu --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\n", "kind: ncs-classification-model\n", "format_version: 1\n", "accepted_values:\n", diff --git a/doc-sources/user-guide/sat-learning/sat-learning.ipynb b/doc-sources/user-guide/sat-learning/sat-learning.ipynb index 8c48a999..e068291e 100644 --- a/doc-sources/user-guide/sat-learning/sat-learning.ipynb +++ b/doc-sources/user-guide/sat-learning/sat-learning.ipynb @@ -22,7 +22,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions\n", "kind: ncs-classification-model\n", "format_version: 1\n", "accepted_values:\n", @@ -58,7 +58,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy max-sat-by-separation\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy max-sat-by-separation\n", "kind: ncs-classification-model\n", "format_version: 1\n", "accepted_values:\n", diff --git a/doc-sources/user-guide/synthetic-data/synthetic-data.ipynb b/doc-sources/user-guide/synthetic-data/synthetic-data.ipynb index 5e42db69..55689c8e 100644 --- a/doc-sources/user-guide/synthetic-data/synthetic-data.ipynb +++ b/doc-sources/user-guide/synthetic-data/synthetic-data.ipynb @@ -14,7 +14,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): lincs generate classification-problem 4 3 --random-seed 57\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs generate classification-problem 4 3 --random-seed 57\n", "kind: classification-problem\n", "format_version: 1\n", "criteria:\n", @@ -63,7 +63,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): lincs generate classification-model problem.yml --random-seed 58 --model-type mrsort\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs generate classification-model problem.yml --random-seed 58 --model-type mrsort\n", "kind: ncs-classification-model\n", "format_version: 1\n", "accepted_values:\n", @@ -101,7 +101,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 59 --misclassified-count 0\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 59 --misclassified-count 0\n", "name,\"Criterion 1\",\"Criterion 2\",\"Criterion 3\",\"Criterion 4\",category\n", "\"Alternative 1\",0.924035132,0.804616809,0.157870576,0.637420833,\"Best category\"\n", "\"Alternative 2\",0.866915047,0.979161799,0.0841569453,0.397855282,\"Best category\"\n", @@ -224,7 +224,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): 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 60 --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\n", + "# Reproduction command (with lincs version 0.11.1-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 60 --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\n", "kind: ncs-classification-model\n", "format_version: 1\n", "accepted_values:\n", diff --git a/integration-tests/all-options-of-problem-generation/all-options-of-problem-generation.ipynb b/integration-tests/all-options-of-problem-generation/all-options-of-problem-generation.ipynb index 309287df..d63d1234 100644 --- a/integration-tests/all-options-of-problem-generation/all-options-of-problem-generation.ipynb +++ b/integration-tests/all-options-of-problem-generation/all-options-of-problem-generation.ipynb @@ -10,7 +10,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): lincs generate classification-problem 4 3 --random-seed 42 --denormalized-min-max --allow-decreasing-criteria\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs generate classification-problem 4 3 --random-seed 42 --denormalized-min-max --allow-decreasing-criteria\n", "kind: classification-problem\n", "format_version: 1\n", "criteria:\n", diff --git a/integration-tests/fail-generating-balanced-alternatives/fail-generating-balanced-alternatives.ipynb b/integration-tests/fail-generating-balanced-alternatives/fail-generating-balanced-alternatives.ipynb index ce1e4fb5..2d77f27f 100644 --- a/integration-tests/fail-generating-balanced-alternatives/fail-generating-balanced-alternatives.ipynb +++ b/integration-tests/fail-generating-balanced-alternatives/fail-generating-balanced-alternatives.ipynb @@ -22,7 +22,7 @@ "output_type": "stream", "text": [ "ERROR: lincs is unable to generate a balanced set of classified alternatives. Try to increase the allowed imbalance, or use a more lenient model?\n", - "Reproduction command (with lincs version 0.11.0): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 42 --max-imbalance 0.0 --misclassified-count 0\n" + "Reproduction command (with lincs version 0.11.1-dev): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 42 --max-imbalance 0.0 --misclassified-count 0\n" ] } ], diff --git a/integration-tests/learning-failure-exception/learning-failure-exception.ipynb b/integration-tests/learning-failure-exception/learning-failure-exception.ipynb index 5d071ea8..6ce01f07 100644 --- a/integration-tests/learning-failure-exception/learning-failure-exception.ipynb +++ b/integration-tests/learning-failure-exception/learning-failure-exception.ipynb @@ -23,7 +23,7 @@ "output_type": "stream", "text": [ "ERROR: lincs is unable to learn from this learning set using this algorithm and these parameters.\n", - "Reproduction command (with lincs version 0.11.0): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions\n" + "Reproduction command (with lincs version 0.11.1-dev): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions\n" ] } ], diff --git a/integration-tests/python-module-is-executable/python-module-is-executable.ipynb b/integration-tests/python-module-is-executable/python-module-is-executable.ipynb index 7b557f9e..8a4da1b7 100644 --- a/integration-tests/python-module-is-executable/python-module-is-executable.ipynb +++ b/integration-tests/python-module-is-executable/python-module-is-executable.ipynb @@ -11,7 +11,7 @@ "output_type": "stream", "text": [ "Python 3.7\n", - "# Reproduction command (with lincs version 0.11.0): lincs generate classification-problem 4 3 --random-seed 208978669\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs generate classification-problem 4 3 --random-seed 208978669\n", "kind: classification-problem\n", "format_version: 1\n", "criteria:\n", @@ -40,7 +40,7 @@ " - name: Intermediate category 1\n", " - name: Best category\n", "Python 3.8\n", - "# Reproduction command (with lincs version 0.11.0): lincs generate classification-problem 4 3 --random-seed 208978669\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs generate classification-problem 4 3 --random-seed 208978669\n", "kind: classification-problem\n", "format_version: 1\n", "criteria:\n", @@ -69,7 +69,7 @@ " - name: Intermediate category 1\n", " - name: Best category\n", "Python 3.9\n", - "# Reproduction command (with lincs version 0.11.0): lincs generate classification-problem 4 3 --random-seed 208978669\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs generate classification-problem 4 3 --random-seed 208978669\n", "kind: classification-problem\n", "format_version: 1\n", "criteria:\n", @@ -98,7 +98,7 @@ " - name: Intermediate category 1\n", " - name: Best category\n", "Python 3.10\n", - "# Reproduction command (with lincs version 0.11.0): lincs generate classification-problem 4 3 --random-seed 208978669\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs generate classification-problem 4 3 --random-seed 208978669\n", "kind: classification-problem\n", "format_version: 1\n", "criteria:\n", @@ -127,7 +127,7 @@ " - name: Intermediate category 1\n", " - name: Best category\n", "Python 3.11\n", - "# Reproduction command (with lincs version 0.11.0): lincs generate classification-problem 4 3 --random-seed 208978669\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs generate classification-problem 4 3 --random-seed 208978669\n", "kind: classification-problem\n", "format_version: 1\n", "criteria:\n", diff --git a/integration-tests/read-from-stdin/read-from-stdin.ipynb b/integration-tests/read-from-stdin/read-from-stdin.ipynb index 12515f87..e7a9d659 100644 --- a/integration-tests/read-from-stdin/read-from-stdin.ipynb +++ b/integration-tests/read-from-stdin/read-from-stdin.ipynb @@ -10,7 +10,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Reproduction command (with lincs version 0.11.0): lincs generate classification-model - --random-seed 45 --model-type mrsort\n", + "# Reproduction command (with lincs version 0.11.1-dev): lincs generate classification-model - --random-seed 45 --model-type mrsort\n", "kind: ncs-classification-model\n", "format_version: 1\n", "accepted_values:\n", diff --git a/integration-tests/verbose/verbose.ipynb b/integration-tests/verbose/verbose.ipynb index deb43906..417e1aa6 100644 --- a/integration-tests/verbose/verbose.ipynb +++ b/integration-tests/verbose/verbose.ipynb @@ -58,7 +58,7 @@ "Best accuracy (after 34 iterations): 198\n", "Best accuracy (after 35 iterations): 198\n", "Final accuracy (after 36 iterations): 200\n", - "# Reproduction command (with lincs version 0.11.0): 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 42 --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\n", + "# Reproduction command (with lincs version 0.11.1-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 42 --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\n", "kind: ncs-classification-model\n", "format_version: 1\n", "accepted_values:\n", diff --git a/lincs/__init__.py b/lincs/__init__.py index 091f94fb..feb72bcd 100644 --- a/lincs/__init__.py +++ b/lincs/__init__.py @@ -1,6 +1,6 @@ # Copyright 2023 Vincent Jacques -__version__ = "0.11.0" +__version__ = "0.11.1-dev" # I/O from liblincs import DataValidationException