Run
9820239

Run 9820239

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)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_sparsetrue
sklearn.svm.classes.SVC(22)_C3.2168208217079246
sklearn.svm.classes.SVC(22)_cache_size200
sklearn.svm.classes.SVC(22)_class_weightnull
sklearn.svm.classes.SVC(22)_coef0-0.9481032221601338
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sklearn.svm.classes.SVC(22)_gamma0.01993721680340372
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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.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)_transformer_weightsnull
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_memorynull
sklearn.feature_selection.variance_threshold.VarianceThreshold(18)_threshold0.0
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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
0.5149 ± 0.0118
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.2758 ± 0.0201
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0274 ± 0.0213
Cross-validation details (10-fold Crossvalidation)
KB relative information score
663.8327 ± 14.8833
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2326 ± 0.01
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
0.2728 ± 0.0498
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.3022 ± 0.0299
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.3005
Cross-validation details (10-fold Crossvalidation)
Recall
0.3022 ± 0.0299
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9275 ± 0.0397
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
0.4823 ± 0.0104
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.3621 ± 0.0291
Cross-validation details (10-fold Crossvalidation)