Run
9644068

Run 9644068

Task 14968 (Supervised Classification) cylinder-bands 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)_copytrue
sklearn.preprocessing.imputation.Imputer(29)_missing_values"NaN"
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sklearn.preprocessing.imputation.Imputer(29)_verbose0
sklearn.preprocessing.data.StandardScaler(14)_copytrue
sklearn.preprocessing.data.StandardScaler(14)_with_meantrue
sklearn.preprocessing.data.StandardScaler(14)_with_stdtrue
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sklearn.impute.SimpleImputer(1)_fill_value-1
sklearn.impute.SimpleImputer(1)_missing_valuesNaN
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sklearn.preprocessing._encoders.OneHotEncoder(3)_categorical_featuresnull
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sklearn.preprocessing._encoders.OneHotEncoder(3)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_sparsetrue
sklearn.svm.classes.SVC(22)_C9671.578923701383
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sklearn.svm.classes.SVC(22)_class_weightnull
sklearn.svm.classes.SVC(22)_coef00.0
sklearn.svm.classes.SVC(22)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(22)_degree3
sklearn.svm.classes.SVC(22)_gamma0.04845050573191216
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"
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
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)_transformer_weightsnull
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_memorynull
sklearn.feature_selection.variance_threshold.VarianceThreshold(18)_threshold0.0
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
0.8462 ± 0.0494
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.853 ± 0.0484
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6978 ± 0.0985
Cross-validation details (10-fold Crossvalidation)
KB relative information score
376.3116 ± 5.3556
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1463 ± 0.0482
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4879 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
Number of instances
540
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8534 ± 0.0478
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8537 ± 0.0482
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9826
Cross-validation details (10-fold Crossvalidation)
Recall
0.8537 ± 0.0482
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2998 ± 0.0987
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4939 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3825 ± 0.0651
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7744 ± 0.1315
Cross-validation details (10-fold Crossvalidation)