Run
9532511

Run 9532511

Task 23 (Supervised Classification) cmc Uploaded 11-10-2018 by Jan van Rijn
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Flow

sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transfo rmer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=s klearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imp uter,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=skle arn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotenco der=sklearn.preprocessing._encoders.OneHotEncoder)),bernoullinb=sklearn.nai ve_bayes.BernoulliNB)(1)Automatically created scikit-learn flow.
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_n_jobsnull
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,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(missingindicator=sklearn.impute.MissingIndicator,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(missingindicator=sklearn.impute.MissingIndicator,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(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_memorynull
sklearn.impute.MissingIndicator(1)_error_on_newfalse
sklearn.impute.MissingIndicator(1)_features"missing-only"
sklearn.impute.MissingIndicator(1)_missing_valuesNaN
sklearn.impute.MissingIndicator(1)_sparse"auto"
sklearn.preprocessing.imputation.Imputer(29)_axis0
sklearn.preprocessing.imputation.Imputer(29)_copytrue
sklearn.preprocessing.imputation.Imputer(29)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(29)_strategy"median"
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
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_memorynull
sklearn.impute.SimpleImputer(1)_copytrue
sklearn.impute.SimpleImputer(1)_fill_value-1
sklearn.impute.SimpleImputer(1)_missing_valuesNaN
sklearn.impute.SimpleImputer(1)_strategy"constant"
sklearn.impute.SimpleImputer(1)_verbose0
sklearn.preprocessing._encoders.OneHotEncoder(3)_categorical_featuresnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_categoriesnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(3)_handle_unknown"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(3)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_sparsetrue
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),bernoullinb=sklearn.naive_bayes.BernoulliNB)(1)_memorynull
sklearn.naive_bayes.BernoulliNB(5)_alpha87.90922561020452
sklearn.naive_bayes.BernoulliNB(5)_binarize0.0
sklearn.naive_bayes.BernoulliNB(5)_class_priornull
sklearn.naive_bayes.BernoulliNB(5)_fit_priorfalse

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
0.6195 ± 0.0277
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.4548 ± 0.0322
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.177 ± 0.0437
Cross-validation details (10-fold Crossvalidation)
KB relative information score
197.3353 ± 3.0918
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4067 ± 0.0085
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4308 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
1473
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.4657 ± 0.0297
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.4549 ± 0.0308
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.5392
Cross-validation details (10-fold Crossvalidation)
Recall
0.4549 ± 0.0308
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.944 ± 0.02
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4641 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.465 ± 0.012
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0019 ± 0.0261
Cross-validation details (10-fold Crossvalidation)