Run
9734330

Run 9734330

Task 3889 (Supervised Classification) sylva_agnostic Uploaded 21-10-2018 by Scikit-learn Bot
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Flow

sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transfo rmer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.pr eprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.St andardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.imput e.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder )),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceT hreshold,svc=sklearn.svm.classes.SVC)(1)Automatically created scikit-learn flow.
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sklearn.svm.classes.SVC(22)_C479.7146029807663
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sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_remainder"passthrough"
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_memorynull
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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.

17 Evaluation measures

Area under ROC curve
0.505 ± 0.0056
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9101 ± 0.0018
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0187 ± 0.0207
Cross-validation details (10-fold Crossvalidation)
KB relative information score
3567.7901 ± 12.8313
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.061 ± 0.001
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1156 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
14395
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9366 ± 0.013
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.939 ± 0.001
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3338
Cross-validation details (10-fold Crossvalidation)
Recall
0.939 ± 0.001
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5277 ± 0.0073
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2403 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.247 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0276 ± 0.0062
Cross-validation details (10-fold Crossvalidation)