Run
10284396

Run 10284396

Task 9985 (Supervised Classification) first-order-theorem-proving Uploaded 29-07-2019 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_regularization10000.0
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_learning_rate0.1
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_loss"auto"
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_max_bins32
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_max_depth5
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_max_iter100
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_max_leaf_nodes8
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_min_samples_leaf35
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_n_iter_no_changenull
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)_random_state58128
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_fraction0.2
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
0.7419 ± 0.016
Per class
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.064 ± 0.0025
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2426 ± 0.0005
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2508 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
6118
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.4175 ± 0.001
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.3 ± 0.0025
Cross-validation details (10-fold Crossvalidation)
Recall
0.4175 ± 0.001
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9675 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3541 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3441 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9718 ± 0.002
Cross-validation details (10-fold Crossvalidation)