Run
9857533

Run 9857533

Task 34536 (Supervised Classification) Internet-Advertisements Uploaded 23-10-2018 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)_C0.07036827535463405
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sklearn.svm.classes.SVC(22)_coef00.0
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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
0.5741 ± 0.031
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8404 ± 0.0169
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2303 ± 0.0879
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1234.8381 ± 14.8868
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1192 ± 0.0085
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2409 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Number of instances
3279
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8953 ± 0.0065
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8808 ± 0.0085
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.5848
Cross-validation details (10-fold Crossvalidation)
Recall
0.8808 ± 0.0085
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4949 ± 0.0355
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.347 ± 0.0009
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3453 ± 0.0122
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9952 ± 0.036
Cross-validation details (10-fold Crossvalidation)