Run
9866880

Run 9866880

Task 9952 (Supervised Classification) phoneme Uploaded 07-12-2018 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,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.Grad ientBoostingClassifier)(1)Automatically created scikit-learn flow.
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,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)_memorynull
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))(2)_n_jobsnull
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))(2)_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))(2)_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))(2)_transformer_weightsnull
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(2)_memorynull
sklearn.preprocessing.imputation.Imputer(31)_axis0
sklearn.preprocessing.imputation.Imputer(31)_copytrue
sklearn.preprocessing.imputation.Imputer(31)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(31)_strategy"median"
sklearn.preprocessing.imputation.Imputer(31)_verbose0
sklearn.preprocessing.data.StandardScaler(17)_copytrue
sklearn.preprocessing.data.StandardScaler(17)_with_meantrue
sklearn.preprocessing.data.StandardScaler(17)_with_stdtrue
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(2)_memorynull
sklearn.impute.SimpleImputer(2)_copytrue
sklearn.impute.SimpleImputer(2)_fill_value-1
sklearn.impute.SimpleImputer(2)_missing_valuesNaN
sklearn.impute.SimpleImputer(2)_strategy"constant"
sklearn.impute.SimpleImputer(2)_verbose0
sklearn.preprocessing._encoders.OneHotEncoder(5)_categorical_featuresnull
sklearn.preprocessing._encoders.OneHotEncoder(5)_categoriesnull
sklearn.preprocessing._encoders.OneHotEncoder(5)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(5)_handle_unknown"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(5)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(5)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(19)_threshold0.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_criterion"friedman_mse"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_initnull
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_learning_rate0.010028323142385841
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_loss"deviance"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_max_depth4
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_max_features0.912042783980391
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_max_leaf_nodesnull
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_impurity_decrease0.43740960541368346
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_impurity_splitnull
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_samples_leaf8
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_samples_split4
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_weight_fraction_leaf0.08991851453409727
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_n_estimators504
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_n_iter_no_change314
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_presort"auto"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_random_state26228
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_subsample0.46319471753700414
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_tol1.1740409643316231e-05
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_validation_fraction0.1067675729250065
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_verbose0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_warm_startfalse

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

0.9123 ± 0.011
Per class
Cross-validation details (10-fold Crossvalidation)
0.8462 ± 0.0205
Per class
Cross-validation details (10-fold Crossvalidation)
0.6255 ± 0.0518
Cross-validation details (10-fold Crossvalidation)
2352.0686 ± 10.9305
Cross-validation details (10-fold Crossvalidation)
0.2374 ± 0.0065
Cross-validation details (10-fold Crossvalidation)
0.4147 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
5404
Per class
Cross-validation details (10-fold Crossvalidation)
0.8454 ± 0.021
Per class
Cross-validation details (10-fold Crossvalidation)
0.8479 ± 0.0195
Cross-validation details (10-fold Crossvalidation)
0.8733
Cross-validation details (10-fold Crossvalidation)
0.8479 ± 0.0195
Per class
Cross-validation details (10-fold Crossvalidation)
0.5724 ± 0.0156
Cross-validation details (10-fold Crossvalidation)
0.4554 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
0.3307 ± 0.0095
Cross-validation details (10-fold Crossvalidation)
0.7262 ± 0.0208
Cross-validation details (10-fold Crossvalidation)