Run
9204365

Run 9204365

Task 49 (Supervised Classification) tic-tac-toe Uploaded 16-08-2018 by Jan van Rijn
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Issue #Downvotes for this reason By


Flow

weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomS earch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(wek a.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsuperv ised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize) ,weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)))(1)Weka implementation.
weka.classifiers.meta.multisearch.RandomSearch(1)_sample-size["100.0"]
weka.classifiers.meta.multisearch.RandomSearch(1)_num-folds["3"]
weka.classifiers.meta.multisearch.RandomSearch(1)_test-set["."]
weka.classifiers.meta.multisearch.RandomSearch(1)_num-iterations["200"]
weka.classifiers.meta.multisearch.RandomSearch(1)_num-slots["20"]
weka.classifiers.meta.multisearch.RandomSearch(1)_D["false"]
weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize)(1)_F["weka.filters.unsupervised.attribute.ReplaceMissingValues","weka.filters.unsupervised.attribute.RemoveUseless","weka.filters.unsupervised.attribute.Normalize"]
weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize)(1)_output-debug-info["false"]
weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize)(1)_-do-not-check-capabilities["false"]
weka.filters.unsupervised.attribute.RemoveUseless(1)_M["99.0"]
weka.filters.unsupervised.attribute.Normalize(1)_S["1.0"]
weka.filters.unsupervised.attribute.Normalize(1)_T["0.0"]
weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)))(1)_E["ACC"]
weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)))(1)_class-label["1"]
weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)))(1)_search["weka.core.setupgenerator.MathParameter -property classifier.numIterations -min 500.0 -max 10000.0 -step 1.0 -base 1.0 -expression I","weka.core.setupgenerator.MathParameter -property classifier.classifier.maxDepth -min 1.0 -max 5.0 -step 1.0 -base 1.0 -expression I","weka.core.setupgenerator.MathParameter -property classifier.shrinkage -min -4.0 -max -1.0 -step 1.0 -base 10.0 -expression pow(BASE,I)"]
weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)))(1)_algorithm["weka.classifiers.meta.multisearch.RandomSearch"]
weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)))(1)_log-file["/home/fr/fr_fr/fr_jv1031"]
weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)))(1)_S["1"]
weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)))(1)_W["weka.classifiers.meta.FilteredClassifier"]
weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)))(1)_output-debug-info["false"]
weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)))(1)_-do-not-check-capabilities["false"]
weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree))(1)_F["weka.filters.MultiFilter"]
weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree))(1)_doNotCheckForModifiedClassAttribute["false"]
weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree))(1)_S["1"]
weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree))(1)_W["weka.classifiers.meta.LogitBoost"]
weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree))(1)_output-debug-info["false"]
weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree))(1)_-do-not-check-capabilities["false"]
weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)(1)_Q["false"]
weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)(1)_use-estimated-priors["false"]
weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)(1)_P["100"]
weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)(1)_L["-1.7976931348623157E308"]
weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)(1)_H["1.0"]
weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)(1)_Z["3.0"]
weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)(1)_O["1"]
weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)(1)_E["1"]
weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)(1)_S["1"]
weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)(1)_I["10"]
weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)(1)_W["weka.classifiers.trees.REPTree"]
weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)(1)_output-debug-info["false"]
weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)(1)_-do-not-check-capabilities["false"]
weka.classifiers.trees.REPTree(1)_M["2"]
weka.classifiers.trees.REPTree(1)_V["0.001"]
weka.classifiers.trees.REPTree(1)_N["3"]
weka.classifiers.trees.REPTree(1)_S["1"]
weka.classifiers.trees.REPTree(1)_P["false"]
weka.classifiers.trees.REPTree(1)_L["-1"]
weka.classifiers.trees.REPTree(1)_I["0.0"]
weka.classifiers.trees.REPTree(1)_R["false"]
weka.classifiers.trees.REPTree(1)_output-debug-info["false"]
weka.classifiers.trees.REPTree(1)_-do-not-check-capabilities["false"]

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

arff
Trace

ARFF file with the trace of all hyperparameter settings tried during optimization, and their performance.

0 Evaluation measures