Run
4560

Run 4560

Task 115 (Supervised Classification) diabetes Uploaded 18-10-2024 by Jan van Rijn
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
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.functions.MultilayerPerceptron))(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["10"]
weka.classifiers.meta.multisearch.RandomSearch(1)_num-slots["1"]
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)_S["1"]
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.functions.MultilayerPerceptron))(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.functions.MultilayerPerceptron))(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.functions.MultilayerPerceptron))(1)_search["weka.core.setupgenerator.MLPLayersParameter -property classifier.hiddenLayers -minLayers 1 -maxLayers 2 -minLayerSize 8 -maxLayerSize 16","weka.core.setupgenerator.MathParameter -property classifier.learningRate -min -5.0 -max 0.0 -step 1.0 -base 10.0 -expression pow(BASE,I)","weka.core.setupgenerator.ListParameter -property classifier.decay -list \"false true\"","weka.core.setupgenerator.MathParameter -property classifier.trainingTime -min 2.0 -max 50.0 -step 1.0 -base 1.0 -expression I","weka.core.setupgenerator.MathParameter -property classifier.momentum -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.functions.MultilayerPerceptron))(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.functions.MultilayerPerceptron))(1)_log-file["/Users/janvanrijn/projects/openml-weka"]
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.functions.MultilayerPerceptron))(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.functions.MultilayerPerceptron))(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.functions.MultilayerPerceptron))(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.functions.MultilayerPerceptron))(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.functions.MultilayerPerceptron)(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.functions.MultilayerPerceptron)(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.functions.MultilayerPerceptron)(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.functions.MultilayerPerceptron)(1)_W["weka.classifiers.functions.MultilayerPerceptron"]
weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.functions.MultilayerPerceptron)(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.functions.MultilayerPerceptron)(1)_-do-not-check-capabilities["false"]
weka.classifiers.functions.MultilayerPerceptron(1)_L["0.3"]
weka.classifiers.functions.MultilayerPerceptron(1)_M["0.2"]
weka.classifiers.functions.MultilayerPerceptron(1)_N["500"]
weka.classifiers.functions.MultilayerPerceptron(1)_V["0"]
weka.classifiers.functions.MultilayerPerceptron(1)_S["0"]
weka.classifiers.functions.MultilayerPerceptron(1)_E["20"]
weka.classifiers.functions.MultilayerPerceptron(1)_G["false"]
weka.classifiers.functions.MultilayerPerceptron(1)_A["false"]
weka.classifiers.functions.MultilayerPerceptron(1)_B["false"]
weka.classifiers.functions.MultilayerPerceptron(1)_H["a"]
weka.classifiers.functions.MultilayerPerceptron(1)_C["false"]
weka.classifiers.functions.MultilayerPerceptron(1)_I["false"]
weka.classifiers.functions.MultilayerPerceptron(1)_R["false"]
weka.classifiers.functions.MultilayerPerceptron(1)_D["false"]
weka.classifiers.functions.MultilayerPerceptron(1)_resume["false"]
weka.classifiers.functions.MultilayerPerceptron(1)_output-debug-info["false"]
weka.classifiers.functions.MultilayerPerceptron(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.

19 Evaluation measures

Area under ROC curve
0.7948 ± 0.0539
Per class
F measure
0.7462 ± 0.0628
Per class
Kappa
0.4351 ± 0.1352
KB relative information score
0.3342 ± 0.1058
Mean absolute error
0.3045 ± 0.0461
Mean prior absolute error
0.4545 ± 0.0011
Weighted recall
0.75 ± 0.0516
Number of instances
768
Per class
OS information
['Homebrew', '23', 'aarch64', 'Mac OS X', '12.5.1']
Precision
0.7449 ± 0.0449
Per class
Predictive accuracy
0.75 ± 0.0516
Prior entropy
0.9331 ± 0.0032
Relative absolute error
0.6699 ± 0.1028
Root mean prior squared error
0.4766 ± 0.0011
Root mean squared error
0.421 ± 0.0405
Root relative squared error
0.8832 ± 0.0859
Unweighted recall
0.7119 ± 0.0717