Run
9868646

Run 9868646

Task 14969 (Supervised Classification) GesturePhaseSegmentationProcessed 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"most_frequent"
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_rate0.03179323812615245
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_loss"deviance"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_max_depth9
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_max_features0.4944759144904701
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_max_leaf_nodesnull
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_impurity_decrease0.3900717206715846
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_impurity_splitnull
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_samples_leaf14
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_samples_split10
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_weight_fraction_leaf0.4614258903953669
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_n_estimators439
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_n_iter_no_change85
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_presort"auto"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_random_state55226
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_subsample0.8315547042102819
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_tol0.0010882035373108463
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_validation_fraction0.8073850713856515
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

Area under ROC curve
0.7442 ± 0.0062
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.4251 ± 0.0168
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2832 ± 0.0189
Cross-validation details (10-fold Crossvalidation)
KB relative information score
2329.0886 ± 5.7711
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2673 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3065 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
9873
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.454 ± 0.0344
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.4788 ± 0.0127
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.1936
Cross-validation details (10-fold Crossvalidation)
Recall
0.4788 ± 0.0127
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8722 ± 0.0043
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3915 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3638 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9293 ± 0.003
Cross-validation details (10-fold Crossvalidation)