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10437599

Run 10437599

Task 146821 (Supervised Classification) car Uploaded 07-02-2020 by Nicolas Hug
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  • openml-python Sklearn_0.23.dev0.
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sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(es timator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGrad ientBoostingClassifier)(3)Randomized search on hyper parameters. The search strategy starts evaluating all the candidates with a small amount of resources and iteratively selects the best candidates, using more and more resources. The candidates are sampled at random from the parameter space and the number of sampled candidates is determined by ``n_candidates``.
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_aggressive_eliminationfalse
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_cv5
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_error_scoreNaN
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_force_exhaust_resourcestrue
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_max_resources"auto"
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_min_resources"auto"
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_n_candidates100
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_n_jobsnull
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_param_distributions{"l2_regularization": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "scipy.stats._continuous_distns.reciprocal_gen", "a": -Infinity, "b": Infinity, "args": [0.0001, 1], "kwds": {}}}, "learning_rate": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "scipy.stats._continuous_distns.reciprocal_gen", "a": -Infinity, "b": Infinity, "args": [0.0001, 1], "kwds": {}}}, "max_depth": [5, 6, 7, 8, 9, 1000], "max_leaf_nodes": [30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "min_samples_leaf": [2, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29]}
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_pre_dispatch"2*n_jobs"
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_random_state0
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_ratio3
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_refit{"oml-python:serialized_object": "function", "value": "sklearn.model_selection._search_successive_halving._refit_callable"}
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_resource"n_samples"
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_return_train_scoretrue
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_scoringnull
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)_verbose0
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_l2_regularization0.0
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_learning_rate0.1
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_loss"auto"
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_max_bins255
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_max_depthnull
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_max_iter100
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_max_leaf_nodes31
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_min_samples_leaf20
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_n_iter_no_changenull
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_random_state32527
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_scoringnull
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_tol1e-07
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_validation_fraction0.1
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_verbose0
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(5)_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.

arff
Trace

ARFF file with the trace of all hyperparameter settings tried during optimization, and their performance.

18 Evaluation measures

Area under ROC curve
1 ± 0
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9994 ± 0.0018
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9987 ± 0.004
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.9959 ± 0.0049
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0015 ± 0.0015
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.229 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.9994 ± 0.0018
Cross-validation details (10-fold Crossvalidation)
Number of instances
1728
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9994 ± 0.0018
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9994 ± 0.0018
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.2058 ± 0.0088
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0064 ± 0.0066
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
0.0178 ± 0.012
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.0526 ± 0.0355
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.9998 ± 0.0007
Cross-validation details (10-fold Crossvalidation)