Run
9809780

Run 9809780

Task 9985 (Supervised Classification) first-order-theorem-proving Uploaded 22-10-2018 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.preprocessing.imputation.Imputer(29)_copytrue
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sklearn.preprocessing.data.StandardScaler(14)_with_meantrue
sklearn.preprocessing.data.StandardScaler(14)_with_stdtrue
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sklearn.preprocessing._encoders.OneHotEncoder(3)_sparsetrue
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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"
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)_sparse_threshold0.3
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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
0.5226 ± 0.0148
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.2881 ± 0.0203
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0419 ± 0.0261
Cross-validation details (10-fold Crossvalidation)
KB relative information score
733.611 ± 11.8038
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2284 ± 0.0073
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2508 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
6118
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.2849 ± 0.0278
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.3148 ± 0.0219
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.3005
Cross-validation details (10-fold Crossvalidation)
Recall
0.3148 ± 0.0219
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9108 ± 0.0292
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3541 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4779 ± 0.0076
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.3497 ± 0.0216
Cross-validation details (10-fold Crossvalidation)