Run
9204438

Run 9204438

Task 3021 (Supervised Classification) sick Uploaded 17-08-2018 by Jan van Rijn
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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.trees.RandomForest))(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.trees.RandomForest))(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.trees.RandomForest))(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.trees.RandomForest))(1)_search["weka.core.setupgenerator.MathParameter -property classifier.numFeatures -min 0.1 -max 0.9 -step 0.1 -base 1.0 -expression 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.trees.RandomForest))(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.trees.RandomForest))(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.trees.RandomForest))(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.trees.RandomForest))(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.trees.RandomForest))(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.trees.RandomForest))(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.trees.RandomForest)(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.trees.RandomForest)(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.trees.RandomForest)(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.trees.RandomForest)(1)_W["weka.classifiers.trees.RandomForest"]
weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.trees.RandomForest)(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.trees.RandomForest)(1)_-do-not-check-capabilities["false"]
weka.classifiers.trees.RandomForest(1)_P["100"]
weka.classifiers.trees.RandomForest(1)_O["false"]
weka.classifiers.trees.RandomForest(1)_store-out-of-bag-predictions["false"]
weka.classifiers.trees.RandomForest(1)_output-out-of-bag-complexity-statistics["false"]
weka.classifiers.trees.RandomForest(1)_print["false"]
weka.classifiers.trees.RandomForest(1)_attribute-importance["false"]
weka.classifiers.trees.RandomForest(1)_I["100"]
weka.classifiers.trees.RandomForest(1)_num-slots["1"]
weka.classifiers.trees.RandomForest(1)_K["0"]
weka.classifiers.trees.RandomForest(1)_M["1.0"]
weka.classifiers.trees.RandomForest(1)_V["0.001"]
weka.classifiers.trees.RandomForest(1)_S["1"]
weka.classifiers.trees.RandomForest(1)_U["false"]
weka.classifiers.trees.RandomForest(1)_B["false"]
weka.classifiers.trees.RandomForest(1)_output-debug-info["false"]
weka.classifiers.trees.RandomForest(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