Run
10219156

Run 10219156

Task 21 (Supervised Classification) car Uploaded 18-04-2019 by Jan van Rijn
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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)(4)Automatically created scikit-learn flow.
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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))(4)_remainder"passthrough"
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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))(4)_transformer_weightsnull
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))(4)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": []}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 1, 2, 3, 4, 5]}}]
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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)(4)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}]
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sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_initnull
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sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_validation_fraction0.18084252020064473
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_verbose0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_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.

15 Evaluation measures

Area under ROC curve
0.2465 ± 0.0042
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
-0.2625 ± 0.02
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-1406.4117 ± 2.4321
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4511 ± 0.0048
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.229 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Number of instances
1728
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.0185 ± 0.0098
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.2099
Cross-validation details (10-fold Crossvalidation)
Recall
0.0185 ± 0.0098
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
1.9699 ± 0.0177
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3381 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.6101 ± 0.0063
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.8045 ± 0.016
Cross-validation details (10-fold Crossvalidation)