Run
9725671

Run 9725671

Task 9985 (Supervised Classification) first-order-theorem-proving 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.preprocessing.imputation.Imputer(29)_copytrue
sklearn.preprocessing.imputation.Imputer(29)_missing_values"NaN"
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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
sklearn.svm.classes.SVC(22)_C14.869737749907479
sklearn.svm.classes.SVC(22)_cache_size200
sklearn.svm.classes.SVC(22)_class_weightnull
sklearn.svm.classes.SVC(22)_coef0-0.7456241984126077
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sklearn.svm.classes.SVC(22)_gamma4.0650654420244035
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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
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
0.4774 ± 0.0151
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.2312 ± 0.021
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
-0.0403 ± 0.0249
Cross-validation details (10-fold Crossvalidation)
KB relative information score
347.3437 ± 15.8697
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2491 ± 0.0108
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
0.2192 ± 0.0175
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.2527 ± 0.0325
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.3005
Cross-validation details (10-fold Crossvalidation)
Recall
0.2527 ± 0.0325
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9934 ± 0.0434
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
0.4991 ± 0.0108
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.4096 ± 0.031
Cross-validation details (10-fold Crossvalidation)