Run
9852016

Run 9852016

Task 36 (Supervised Classification) segment 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.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)_C139.81454081203555
sklearn.svm.classes.SVC(22)_cache_size200
sklearn.svm.classes.SVC(22)_class_weightnull
sklearn.svm.classes.SVC(22)_coef00.832021917737163
sklearn.svm.classes.SVC(22)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(22)_degree3
sklearn.svm.classes.SVC(22)_gamma0.00020607585420920482
sklearn.svm.classes.SVC(22)_kernel"sigmoid"
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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
0.95 ± 0.0111
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9137 ± 0.0192
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9 ± 0.0222
Cross-validation details (10-fold Crossvalidation)
KB relative information score
2096.3149 ± 4.7398
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0245 ± 0.0054
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2449
Cross-validation details (10-fold Crossvalidation)
Number of instances
2310
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9144 ± 0.021
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9143 ± 0.019
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.8074
Cross-validation details (10-fold Crossvalidation)
Recall
0.9143 ± 0.019
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1 ± 0.0222
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3499
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1565 ± 0.0173
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4472 ± 0.0496
Cross-validation details (10-fold Crossvalidation)