Changes behavior slightly Optimize WPB model weights before evaluating and returning them
Breaking Add parameter weights_optimization_strategy to the ReinitializeLeastAccurate breeding strategy (required to fix previous point)
# Reproduction command (with lincs version 2.0.0a4): lincs generate classification-problem 4 3 --random-seed 40
+# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 4 3 --random-seed 40
kind: classification-problem
format_version: 1
criteria:
@@ -139,7 +139,7 @@ Get lincs# Reproduction command (with lincs version 2.0.0a4): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort
+# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort
kind: ncs-classification-model
format_version: 1
accepted_values:
@@ -188,7 +188,7 @@ Get lincsreference documentation.
It should start with something like this, and contain 1000 alternatives:
-# Reproduction command (with lincs version 2.0.0a4): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0
+# Reproduction command (with lincs version 2.0.0a5): 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"
@@ -211,7 +211,7 @@ Get lincs# Reproduction command (with lincs version 2.0.0a4): 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 2.0.0a5): 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/docs/get-started.ipynb b/docs/get-started.ipynb
index 82d944df..aa57888f 100644
--- a/docs/get-started.ipynb
+++ b/docs/get-started.ipynb
@@ -48,7 +48,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a4): lincs generate classification-problem 4 3 --random-seed 40\n",
+ "# Reproduction command (with lincs version 2.0.0a5): 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 2.0.0a4): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort\n",
+ "# Reproduction command (with lincs version 2.0.0a5): 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",
@@ -211,7 +211,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a4): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0\n",
+ "# Reproduction command (with lincs version 2.0.0a5): 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",
@@ -260,7 +260,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a4): 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 2.0.0a5): 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/docs/index.html b/docs/index.html
index 2425e90f..9ebdac70 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -5,11 +5,11 @@
- README — lincs 2.0.0a4 documentation
+ README — lincs 2.0.0a5 documentation
-
+
diff --git a/docs/py-modindex.html b/docs/py-modindex.html
index a45927b7..ccf45776 100644
--- a/docs/py-modindex.html
+++ b/docs/py-modindex.html
@@ -4,11 +4,11 @@
- Python Module Index — lincs 2.0.0a4 documentation
+ Python Module Index — lincs 2.0.0a5 documentation
-
+
diff --git a/docs/python-api.html b/docs/python-api.html
index 1f5965a0..70b8a9b2 100644
--- a/docs/python-api.html
+++ b/docs/python-api.html
@@ -5,11 +5,11 @@
- The Python API — lincs 2.0.0a4 documentation
+ The Python API — lincs 2.0.0a5 documentation
-
+
diff --git a/docs/reference.html b/docs/reference.html
index 35ba663a..b886c216 100644
--- a/docs/reference.html
+++ b/docs/reference.html
@@ -5,11 +5,11 @@
- Reference — lincs 2.0.0a4 documentation
+ Reference — lincs 2.0.0a5 documentation
-
+
diff --git a/docs/reference/lincs.html b/docs/reference/lincs.html
index e2af100e..694e2d64 100644
--- a/docs/reference/lincs.html
+++ b/docs/reference/lincs.html
@@ -5,11 +5,11 @@
- The lincs package — lincs 2.0.0a4 documentation
+ The lincs package — lincs 2.0.0a5 documentation
-
+
diff --git a/docs/roadmap.html b/docs/roadmap.html
index 24e8dfe1..89491306 100644
--- a/docs/roadmap.html
+++ b/docs/roadmap.html
@@ -5,11 +5,11 @@
- Roadmap — lincs 2.0.0a4 documentation
+ Roadmap — lincs 2.0.0a5 documentation
-
+
diff --git a/docs/search.html b/docs/search.html
index 49df74c9..0461222f 100644
--- a/docs/search.html
+++ b/docs/search.html
@@ -4,12 +4,12 @@
- Search — lincs 2.0.0a4 documentation
+ Search — lincs 2.0.0a5 documentation
-
+
diff --git a/docs/searchindex.js b/docs/searchindex.js
index 415117d8..539c9cdf 100644
--- a/docs/searchindex.js
+++ b/docs/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"docnames": ["README", "changelog", "conceptual-overview", "contributor-guide", "get-started", "index", "python-api", "reference", "reference/lincs", "roadmap", "single-peaked", "user-guide"], "filenames": ["README.rst", "changelog.rst", "conceptual-overview.rst", "contributor-guide.rst", "get-started.rst", "index.rst", "python-api.md", "reference.rst", "reference/lincs.rst", "roadmap.rst", "single-peaked.rst", "user-guide.rst"], "titles": ["Contributors", "Changelog", "Conceptual overview", "Contributor guide", "Get started", "README", "The Python API", "Reference", "The lincs package", "Roadmap", "Single-peaked criteria", "User Guide"], "terms": {"learn": [0, 1, 3, 4, 5, 8, 9, 10], "infer": [0, 4, 5, 7], "non": [0, 4, 5, 7], "compensatori": [0, 4, 5, 7], "sort": [0, 1, 4, 5, 6, 7, 8, 9, 11], "i": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], "collect": [0, 5], "command": [0, 1, 3, 5, 11], "line": [0, 1, 3, 5, 11], "util": [0, 5], "through": [0, 3, 4, 5, 6], "python": [0, 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\ No newline at end of file
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"lincs.classification.Criterion.real_values"], [8, "lincs.classification.Criterion.real_values"]], "roots (lincs.classification.sufficientcoalitions property)": [[7, "lincs.classification.SufficientCoalitions.roots"], [8, "lincs.classification.SufficientCoalitions.roots"]], "roots (lincs.classification.sufficientcoalitions.kind property)": [[7, "lincs.classification.SufficientCoalitions.Kind.roots"], [8, "lincs.classification.SufficientCoalitions.Kind.roots"]], "single_peaked (lincs.classification.criterion.preferencedirection property)": [[7, "lincs.classification.Criterion.PreferenceDirection.single_peaked"], [8, "lincs.classification.Criterion.PreferenceDirection.single_peaked"]], "single_peaked (lincs.classification.preprocessedlearningset property)": [[7, "lincs.classification.PreprocessedLearningSet.single_peaked"], [8, "lincs.classification.PreprocessedLearningSet.single_peaked"]], "sufficient_coalitions (lincs.classification.model property)": [[7, "lincs.classification.Model.sufficient_coalitions"], [8, "lincs.classification.Model.sufficient_coalitions"]], "terminate() (lincs.classification.learnmrsortbyweightsprofilesbreed.terminationstrategy method)": [[7, "lincs.classification.LearnMrsortByWeightsProfilesBreed.TerminationStrategy.terminate"], [8, "lincs.classification.LearnMrsortByWeightsProfilesBreed.TerminationStrategy.terminate"]], "terminate() (lincs.classification.terminateafteriterations method)": [[7, "lincs.classification.TerminateAfterIterations.terminate"], [8, "lincs.classification.TerminateAfterIterations.terminate"]], "terminate() (lincs.classification.terminateafteriterationswithoutprogress method)": [[7, "lincs.classification.TerminateAfterIterationsWithoutProgress.terminate"], [8, "lincs.classification.TerminateAfterIterationsWithoutProgress.terminate"]], "terminate() (lincs.classification.terminateafterseconds method)": [[7, "lincs.classification.TerminateAfterSeconds.terminate"], [8, "lincs.classification.TerminateAfterSeconds.terminate"]], "terminate() (lincs.classification.terminateaftersecondswithoutprogress method)": [[7, "lincs.classification.TerminateAfterSecondsWithoutProgress.terminate"], [8, "lincs.classification.TerminateAfterSecondsWithoutProgress.terminate"]], "terminate() (lincs.classification.terminateataccuracy method)": [[7, "lincs.classification.TerminateAtAccuracy.terminate"], [8, "lincs.classification.TerminateAtAccuracy.terminate"]], "terminate() (lincs.classification.terminatewhenany method)": [[7, "lincs.classification.TerminateWhenAny.terminate"], [8, "lincs.classification.TerminateWhenAny.terminate"]], "thresholds (lincs.classification.acceptedvalues.enumeratedthresholds property)": [[7, "lincs.classification.AcceptedValues.EnumeratedThresholds.thresholds"], [8, "lincs.classification.AcceptedValues.EnumeratedThresholds.thresholds"]], "thresholds (lincs.classification.acceptedvalues.integerthresholds property)": [[7, "lincs.classification.AcceptedValues.IntegerThresholds.thresholds"], [8, "lincs.classification.AcceptedValues.IntegerThresholds.thresholds"]], "thresholds (lincs.classification.acceptedvalues.kind property)": [[7, "lincs.classification.AcceptedValues.Kind.thresholds"], [8, "lincs.classification.AcceptedValues.Kind.thresholds"]], "thresholds (lincs.classification.acceptedvalues.realthresholds property)": [[7, "lincs.classification.AcceptedValues.RealThresholds.thresholds"], [8, "lincs.classification.AcceptedValues.RealThresholds.thresholds"]], "unchanged (lincs.classification.classificationresult property)": [[7, "lincs.classification.ClassificationResult.unchanged"], [8, "lincs.classification.ClassificationResult.unchanged"]], "upset_roots (lincs.classification.sufficientcoalitions.roots property)": [[7, "lincs.classification.SufficientCoalitions.Roots.upset_roots"], [8, "lincs.classification.SufficientCoalitions.Roots.upset_roots"]], "value (lincs.classification.performance.enumerated property)": [[7, "lincs.classification.Performance.Enumerated.value"], [8, "lincs.classification.Performance.Enumerated.value"]], "value (lincs.classification.performance.integer property)": [[7, "lincs.classification.Performance.Integer.value"], [8, "lincs.classification.Performance.Integer.value"]], "value (lincs.classification.performance.real property)": [[7, "lincs.classification.Performance.Real.value"], [8, "lincs.classification.Performance.Real.value"]], "value_type (lincs.classification.acceptedvalues property)": [[7, "lincs.classification.AcceptedValues.value_type"], [8, "lincs.classification.AcceptedValues.value_type"]], "value_type (lincs.classification.criterion property)": [[7, "lincs.classification.Criterion.value_type"], [8, "lincs.classification.Criterion.value_type"]], "value_type (lincs.classification.performance property)": [[7, "lincs.classification.Performance.value_type"], [8, "lincs.classification.Performance.value_type"]], "values_counts (lincs.classification.preprocessedlearningset property)": [[7, "lincs.classification.PreprocessedLearningSet.values_counts"], [8, "lincs.classification.PreprocessedLearningSet.values_counts"]], "visualize_model() (in module lincs.classification)": [[7, "lincs.classification.visualize_model"], [8, "lincs.classification.visualize_model"]], "weights (lincs.classification.learnmrsortbyweightsprofilesbreed.modelsbeinglearned property)": [[7, "lincs.classification.LearnMrsortByWeightsProfilesBreed.ModelsBeingLearned.weights"], [8, "lincs.classification.LearnMrsortByWeightsProfilesBreed.ModelsBeingLearned.weights"]], "weights (lincs.classification.sufficientcoalitions property)": [[7, "lincs.classification.SufficientCoalitions.weights"], [8, "lincs.classification.SufficientCoalitions.weights"]], "weights (lincs.classification.sufficientcoalitions.kind property)": [[7, "lincs.classification.SufficientCoalitions.Kind.weights"], [8, "lincs.classification.SufficientCoalitions.Kind.weights"]]}})
\ No newline at end of file
diff --git a/docs/single-peaked.html b/docs/single-peaked.html
index 59720722..2d357382 100644
--- a/docs/single-peaked.html
+++ b/docs/single-peaked.html
@@ -5,11 +5,11 @@
- Single-peaked criteria — lincs 2.0.0a4 documentation
+ Single-peaked criteria — lincs 2.0.0a5 documentation
-
+
diff --git a/docs/user-guide.html b/docs/user-guide.html
index 3a7efc66..c419fd64 100644
--- a/docs/user-guide.html
+++ b/docs/user-guide.html
@@ -5,11 +5,11 @@
- User Guide — lincs 2.0.0a4 documentation
+ User Guide — lincs 2.0.0a5 documentation
-
+
@@ -444,7 +444,7 @@ SAT-based strategies
They produce a different kind of model, with the sufficient coalitions specified explicitly by their roots:
-# Reproduction command (with lincs version 2.0.0a4): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions
+# Reproduction command (with lincs version 2.0.0a5): 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/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 a7c4647d..7783bbc0 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 2.0.0a5.dev0): lincs generate classification-problem 4 2 --random-seed 524098961\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 4 2 --random-seed 524098961\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
@@ -54,7 +54,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 2 --random-seed 707823420 --denormalized-min-max\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 4 2 --random-seed 707823420 --denormalized-min-max\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
@@ -98,7 +98,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 2 --random-seed 927184643 --allow-decreasing-criteria\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 4 2 --random-seed 927184643 --allow-decreasing-criteria\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
@@ -142,7 +142,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 2 --random-seed 42 --denormalized-min-max --allow-decreasing-criteria\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 4 2 --random-seed 42 --denormalized-min-max --allow-decreasing-criteria\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
@@ -186,7 +186,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 2 --random-seed 995908924 --forbid-increasing-criteria --allow-decreasing-criteria\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 4 2 --random-seed 995908924 --forbid-increasing-criteria --allow-decreasing-criteria\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
@@ -230,7 +230,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 2 --random-seed 21600946 --forbid-real-criteria --allow-integer-criteria\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 4 2 --random-seed 21600946 --forbid-real-criteria --allow-integer-criteria\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
@@ -274,7 +274,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 2 --random-seed 630859863 --denormalized-min-max --forbid-real-criteria --allow-integer-criteria\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 4 2 --random-seed 630859863 --denormalized-min-max --forbid-real-criteria --allow-integer-criteria\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
@@ -318,7 +318,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 2 --random-seed 958501765 --forbid-real-criteria --allow-enumerated-criteria\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 4 2 --random-seed 958501765 --forbid-real-criteria --allow-enumerated-criteria\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
@@ -354,7 +354,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 2 --random-seed 765795324 --allow-enumerated-criteria --allow-integer-criteria\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 4 2 --random-seed 765795324 --allow-enumerated-criteria --allow-integer-criteria\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
@@ -394,7 +394,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 2 --random-seed 608871414 --denormalized-min-max --allow-enumerated-criteria --allow-integer-criteria\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 4 2 --random-seed 608871414 --denormalized-min-max --allow-enumerated-criteria --allow-integer-criteria\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
diff --git a/integration-tests/enumerated-criteria/enumerated-criteria.ipynb b/integration-tests/enumerated-criteria/enumerated-criteria.ipynb
index 4b6c5ae2..eafda824 100644
--- a/integration-tests/enumerated-criteria/enumerated-criteria.ipynb
+++ b/integration-tests/enumerated-criteria/enumerated-criteria.ipynb
@@ -10,7 +10,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 2 2 --random-seed 520326314 --denormalized-min-max --forbid-real-criteria --allow-enumerated-criteria\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 2 2 --random-seed 520326314 --denormalized-min-max --forbid-real-criteria --allow-enumerated-criteria\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
@@ -68,7 +68,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-model problem.yml --random-seed 564532967 --model-type mrsort\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-model problem.yml --random-seed 564532967 --model-type mrsort\n",
"kind: ncs-classification-model\n",
"format_version: 1\n",
"accepted_values:\n",
@@ -138,7 +138,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 992594045 --max-imbalance 0.1 --misclassified-count 0\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 992594045 --max-imbalance 0.1 --misclassified-count 0\n",
"name,\"Criterion 1\",\"Criterion 2\",category\n",
"\"Alternative 1\",tuz,piz,\"Best category\"\n",
"\"Alternative 2\",got,piz,\"Worst category\"\n",
@@ -202,7 +202,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs learn classification-model problem.yml alternatives.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 1022618183 --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 2.0.0a5): lincs learn classification-model problem.yml alternatives.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 1022618183 --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/fail-generating-balanced-alternatives/fail-generating-balanced-alternatives.ipynb b/integration-tests/fail-generating-balanced-alternatives/fail-generating-balanced-alternatives.ipynb
index 0fc7e2dc..2bd07892 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 2.0.0a5.dev0): 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 2.0.0a5): 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/in-house-simplex-on-cpu-learning/in-house-simplex-on-cpu-learning.ipynb b/integration-tests/in-house-simplex-on-cpu-learning/in-house-simplex-on-cpu-learning.ipynb
index e981fb73..6bf67a75 100644
--- a/integration-tests/in-house-simplex-on-cpu-learning/in-house-simplex-on-cpu-learning.ipynb
+++ b/integration-tests/in-house-simplex-on-cpu-learning/in-house-simplex-on-cpu-learning.ipynb
@@ -22,7 +22,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): 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 341107996 --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 experimental-in-house-simplex --mrsort.weights-profiles-breed.linear-program.experimental-in-house-simplex.processor cpu --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 0.8\n",
+ "# Reproduction command (with lincs version 2.0.0a5): 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 341107996 --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 experimental-in-house-simplex --mrsort.weights-profiles-breed.linear-program.experimental-in-house-simplex.processor cpu --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 0.8\n",
"kind: ncs-classification-model\n",
"format_version: 1\n",
"accepted_values:\n",
diff --git a/integration-tests/in-house-simplex-on-gpu-learning/in-house-simplex-on-gpu-learning.ipynb b/integration-tests/in-house-simplex-on-gpu-learning/in-house-simplex-on-gpu-learning.ipynb
index bb28eb63..9dddc453 100644
--- a/integration-tests/in-house-simplex-on-gpu-learning/in-house-simplex-on-gpu-learning.ipynb
+++ b/integration-tests/in-house-simplex-on-gpu-learning/in-house-simplex-on-gpu-learning.ipynb
@@ -22,7 +22,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): 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 255380809 --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 experimental-in-house-simplex --mrsort.weights-profiles-breed.linear-program.experimental-in-house-simplex.processor gpu --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 0.8\n",
+ "# Reproduction command (with lincs version 2.0.0a5): 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 255380809 --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 experimental-in-house-simplex --mrsort.weights-profiles-breed.linear-program.experimental-in-house-simplex.processor gpu --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 0.8\n",
"kind: ncs-classification-model\n",
"format_version: 1\n",
"accepted_values:\n",
diff --git a/integration-tests/integer-criteria/integer-criteria.ipynb b/integration-tests/integer-criteria/integer-criteria.ipynb
index fe6cd5aa..da429d6f 100644
--- a/integration-tests/integer-criteria/integer-criteria.ipynb
+++ b/integration-tests/integer-criteria/integer-criteria.ipynb
@@ -10,7 +10,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 2 2 --random-seed 535747649 --denormalized-min-max --allow-decreasing-criteria --forbid-real-criteria --allow-integer-criteria\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 2 2 --random-seed 535747649 --denormalized-min-max --allow-decreasing-criteria --forbid-real-criteria --allow-integer-criteria\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
@@ -73,7 +73,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-model problem.yml --random-seed 86476259 --model-type mrsort\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-model problem.yml --random-seed 86476259 --model-type mrsort\n",
"kind: ncs-classification-model\n",
"format_version: 1\n",
"accepted_values:\n",
@@ -143,7 +143,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 148697048 --max-imbalance 0.1 --misclassified-count 0\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 148697048 --max-imbalance 0.1 --misclassified-count 0\n",
"name,\"Criterion 1\",\"Criterion 2\",category\n",
"\"Alternative 1\",9487,4222,\"Worst category\"\n",
"\"Alternative 2\",4230,-4300,\"Worst category\"\n",
@@ -207,7 +207,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs learn classification-model problem.yml alternatives.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 37425142 --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 2.0.0a5): lincs learn classification-model problem.yml alternatives.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 37425142 --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/learning-failure-exception/learning-failure-exception.ipynb b/integration-tests/learning-failure-exception/learning-failure-exception.ipynb
index 31f70c65..0a08ad5a 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 2.0.0a5.dev0): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions\n"
+ "Reproduction command (with lincs version 2.0.0a5): 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 5a67db98..91eb9dd3 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 3.8\n",
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 3 --random-seed 208978669\n",
+ "# Reproduction command (with lincs version 2.0.0a5): 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 3.9\n",
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 3 --random-seed 208978669\n",
+ "# Reproduction command (with lincs version 2.0.0a5): 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 3.10\n",
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 3 --random-seed 208978669\n",
+ "# Reproduction command (with lincs version 2.0.0a5): 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 3.11\n",
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 3 --random-seed 208978669\n",
+ "# Reproduction command (with lincs version 2.0.0a5): 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 3.12\n",
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 3 --random-seed 208978669\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 4 3 --random-seed 208978669\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
@@ -156,7 +156,7 @@
" - name: Intermediate category 1\n",
" - name: Best category\n",
"Python 3.13\n",
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 4 3 --random-seed 208978669\n",
+ "# Reproduction command (with lincs version 2.0.0a5): 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 c27d1d90..2ca35d75 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 2.0.0a5.dev0): lincs generate classification-model - --random-seed 45 --model-type mrsort\n",
+ "# Reproduction command (with lincs version 2.0.0a5): 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/real-criteria/real-criteria.ipynb b/integration-tests/real-criteria/real-criteria.ipynb
index f1428692..898e22a8 100644
--- a/integration-tests/real-criteria/real-criteria.ipynb
+++ b/integration-tests/real-criteria/real-criteria.ipynb
@@ -10,7 +10,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 2 2 --random-seed 215214479 --denormalized-min-max --allow-decreasing-criteria\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 2 2 --random-seed 215214479 --denormalized-min-max --allow-decreasing-criteria\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
@@ -72,7 +72,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-model problem.yml --random-seed 327117407 --model-type mrsort\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-model problem.yml --random-seed 327117407 --model-type mrsort\n",
"kind: ncs-classification-model\n",
"format_version: 1\n",
"accepted_values:\n",
@@ -142,7 +142,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 802416786 --max-imbalance 0.1 --misclassified-count 0\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 802416786 --max-imbalance 0.1 --misclassified-count 0\n",
"name,\"Criterion 1\",\"Criterion 2\",category\n",
"\"Alternative 1\",-9.46884727,49.2470016,\"Best category\"\n",
"\"Alternative 2\",-12.0502529,-8.51298046,\"Worst category\"\n",
@@ -206,7 +206,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs learn classification-model problem.yml alternatives.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 80847949 --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 2.0.0a5): lincs learn classification-model problem.yml alternatives.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 80847949 --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/single-peaked-criteria/single-peaked-criteria.ipynb b/integration-tests/single-peaked-criteria/single-peaked-criteria.ipynb
index 50a49fad..462d2e6f 100644
--- a/integration-tests/single-peaked-criteria/single-peaked-criteria.ipynb
+++ b/integration-tests/single-peaked-criteria/single-peaked-criteria.ipynb
@@ -10,7 +10,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-problem 2 2 --random-seed 134400191 --forbid-increasing-criteria --allow-single-peaked-criteria --allow-integer-criteria\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-problem 2 2 --random-seed 134400191 --forbid-increasing-criteria --allow-single-peaked-criteria --allow-integer-criteria\n",
"kind: classification-problem\n",
"format_version: 1\n",
"criteria:\n",
@@ -72,7 +72,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classification-model problem.yml --random-seed 86476259 --model-type mrsort\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classification-model problem.yml --random-seed 86476259 --model-type mrsort\n",
"kind: ncs-classification-model\n",
"format_version: 1\n",
"accepted_values:\n",
@@ -142,7 +142,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 148697048 --max-imbalance 0.1 --misclassified-count 0\n",
+ "# Reproduction command (with lincs version 2.0.0a5): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 148697048 --max-imbalance 0.1 --misclassified-count 0\n",
"name,\"Criterion 1\",\"Criterion 2\",category\n",
"\"Alternative 1\",97,0.728948653,\"Best category\"\n",
"\"Alternative 2\",62,0.268311262,\"Best category\"\n",
@@ -206,7 +206,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "# Reproduction command (with lincs version 2.0.0a5.dev0): lincs learn classification-model problem.yml alternatives.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 37425142 --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 2.0.0a5): lincs learn classification-model problem.yml alternatives.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 37425142 --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/verbose/verbose.ipynb b/integration-tests/verbose/verbose.ipynb
index 32700761..988630db 100644
--- a/integration-tests/verbose/verbose.ipynb
+++ b/integration-tests/verbose/verbose.ipynb
@@ -30,7 +30,7 @@
"Best accuracy (after 6 iterations): 192\n",
"Best accuracy (after 7 iterations): 198\n",
"Final accuracy (after 8 iterations): 200\n",
- "# Reproduction command (with lincs version 2.0.0a5.dev0): 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 2.0.0a5): 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",
@@ -73,7 +73,7 @@
"Best accuracy (after 1 iterations): 183\n",
"Best accuracy (after 2 iterations): 184\n",
"Final accuracy (after 3 iterations): 186\n",
- "# Reproduction command (with lincs version 2.0.0a5.dev0): 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 --mrsort.weights-profiles-breed.max-iterations 3\n",
+ "# Reproduction command (with lincs version 2.0.0a5): 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 --mrsort.weights-profiles-breed.max-iterations 3\n",
"kind: ncs-classification-model\n",
"format_version: 1\n",
"accepted_values:\n",
@@ -122,7 +122,7 @@
"Best accuracy (after 6 iterations): 190\n",
"Best accuracy (after 7 iterations): 190\n",
"Final accuracy (after 8 iterations): 190\n",
- "# Reproduction command (with lincs version 2.0.0a5.dev0): 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 --mrsort.weights-profiles-breed.max-iterations-without-progress 3\n",
+ "# Reproduction command (with lincs version 2.0.0a5): 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 --mrsort.weights-profiles-breed.max-iterations-without-progress 3\n",
"kind: ncs-classification-model\n",
"format_version: 1\n",
"accepted_values:\n",
diff --git a/lincs/__init__.py b/lincs/__init__.py
index 7d4fcedf..cb240794 100644
--- a/lincs/__init__.py
+++ b/lincs/__init__.py
@@ -18,7 +18,7 @@
from . import classification
# General information
-__version__ = "2.0.0a5.dev0"
+__version__ = "2.0.0a5"
has_gpu = hasattr(classification, "ImproveProfilesWithAccuracyHeuristicOnGpu")
try: