Run
9792011

Run 9792011

Task 3948 (Supervised Classification) KDDCup09_upselling 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._encoders.OneHotEncoder(3)_sparsetrue
sklearn.svm.classes.SVC(22)_C15.713145332893864
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sklearn.svm.classes.SVC(22)_class_weightnull
sklearn.svm.classes.SVC(22)_coef0-0.3983525023873742
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sklearn.svm.classes.SVC(22)_gamma0.0004327289952802295
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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
0.518 ± 0.0057
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8954 ± 0.0021
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0611 ± 0.0192
Cross-validation details (10-fold Crossvalidation)
KB relative information score
11454.1852 ± 81.6232
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0755 ± 0.0016
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1364 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
50000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8886 ± 0.0079
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9245 ± 0.0016
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3794
Cross-validation details (10-fold Crossvalidation)
Recall
0.9245 ± 0.0016
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5533 ± 0.0117
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2612 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2748 ± 0.0029
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.052 ± 0.0112
Cross-validation details (10-fold Crossvalidation)