Run
10437697

Run 10437697

Task 3913 (Supervised Classification) kc2 Uploaded 09-02-2020 by Nicolas Hug
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  • openml-python Sklearn_0.23.dev0.
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sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemb le._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier )(4)Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "predict", "predict_proba", "decision_function", "transform" and "inverse_transform" if they are implemented in the estimator used. The parameters of the estimator used to apply these methods are optimized by cross-validated search over parameter settings. In contrast to GridSearchCV, not all parameter values are tried out, but rather a fixed number of parameter settings is sampled from the specified distributions. The number of parameter settings that are tried is given by n_iter. If all parameters are presented as a list, sampling without replacement is performed. If at least one parameter is given as a distribution, sampling with replacement is used. It is highly recommended to use continuous distributions for continuous parameters.
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_state49497
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
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)_cvnull
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)_error_scoreNaN
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)_iid"deprecated"
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)_n_iter100
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)_n_jobsnull
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)_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.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)_pre_dispatch"2*n_jobs"
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)_random_state0
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)_refittrue
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)_return_train_scorefalse
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)_scoringnull
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)_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.

arff
Trace

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

18 Evaluation measures

0.8194 ± 0.1034
Per class
Cross-validation details (10-fold Crossvalidation)
0.832 ± 0.0612
Per class
Cross-validation details (10-fold Crossvalidation)
0.4579 ± 0.189
Cross-validation details (10-fold Crossvalidation)
0.2714 ± 0.1308
Cross-validation details (10-fold Crossvalidation)
0.2209 ± 0.0337
Cross-validation details (10-fold Crossvalidation)
0.3266 ± 0.0052
Cross-validation details (10-fold Crossvalidation)
0.8429 ± 0.0568
Cross-validation details (10-fold Crossvalidation)
522
Per class
Cross-validation details (10-fold Crossvalidation)
0.8303 ± 0.0599
Per class
Cross-validation details (10-fold Crossvalidation)
0.8429 ± 0.0568
Cross-validation details (10-fold Crossvalidation)
0.7318 ± 0.0173
Cross-validation details (10-fold Crossvalidation)
0.6763 ± 0.1017
Cross-validation details (10-fold Crossvalidation)
0.4037 ± 0.0065
Cross-validation details (10-fold Crossvalidation)
0.3377 ± 0.0463
Cross-validation details (10-fold Crossvalidation)
0.8365 ± 0.1087
Cross-validation details (10-fold Crossvalidation)
0.7035 ± 0.0955
Cross-validation details (10-fold Crossvalidation)