Run
9626796

Run 9626796

Task 9914 (Supervised Classification) wilt Uploaded 20-10-2018 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)_missing_values"NaN"
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sklearn.preprocessing.data.StandardScaler(14)_with_meantrue
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sklearn.preprocessing._encoders.OneHotEncoder(3)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_sparsetrue
sklearn.svm.classes.SVC(22)_C5158.225103120233
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sklearn.svm.classes.SVC(22)_coef00.0
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sklearn.svm.classes.SVC(22)_gamma0.0001668828212122635
sklearn.svm.classes.SVC(22)_kernel"rbf"
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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.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_memorynull
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sklearn.pipeline.Pipeline(columntransformer=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)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,svc=sklearn.svm.classes.SVC)(1)_memorynull

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
0.8359 ± 0.0495
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9753 ± 0.0065
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7459 ± 0.0725
Cross-validation details (10-fold Crossvalidation)
KB relative information score
3231.177 ± 40.2943
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0234 ± 0.0058
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1022 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Number of instances
4839
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9753 ± 0.0067
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9766 ± 0.0058
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3037
Cross-validation details (10-fold Crossvalidation)
Recall
0.9766 ± 0.0058
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2284 ± 0.0567
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2259 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1528 ± 0.0189
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6765 ± 0.0847
Cross-validation details (10-fold Crossvalidation)