Run
10261017

Run 10261017

Task 14965 (Supervised Classification) bank-marketing Uploaded 28-07-2019 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer, histgradientboostingclassifier=sklearn.ensemble._hist_gradient_boosting.gra dient_boosting.HistGradientBoostingClassifier)(1)Automatically created scikit-learn flow.
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_l2_regularization0.0001
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_learning_rate0.001
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_loss"auto"
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_max_bins8
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_max_depth18
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_max_iter150
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_max_leaf_nodes32
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_min_samples_leaf24
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_n_iter_no_changenull
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_random_state9512
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_scoringnull
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_tol1e-07
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_validation_fraction0.1
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_verbose0
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,histgradientboostingclassifier=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,histgradientboostingclassifier=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "histgradientboostingclassifier", "step_name": "histgradientboostingclassifier"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,histgradientboostingclassifier=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1)_verbosefalse
sklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(1)_copytrue
sklearn.impute._base.SimpleImputer(1)_fill_valuenull
sklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(1)_strategy"most_frequent"
sklearn.impute._base.SimpleImputer(1)_verbose0

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
0.8854 ± 0.0104
Per class
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.0185 ± 0.0044
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1981 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2066 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
45211
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.883 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.5206 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Recall
0.883 ± 0.0001
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9588 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3214 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3089 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.961 ± 0.0014
Cross-validation details (10-fold Crossvalidation)