Run
10437381

Run 10437381

Task 3560 (Supervised Classification) analcatdata_dmft Uploaded 06-02-2020 by Nicolas Hug
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  • openml-python Sklearn_0.23.dev0.
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Flow

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_state22683
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
0.5634 ± 0.0515
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.2206 ± 0.0613
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0638 ± 0.0681
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.0723 ± 0.0388
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2733 ± 0.0053
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2774 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.2246 ± 0.0568
Cross-validation details (10-fold Crossvalidation)
Number of instances
797
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.2244 ± 0.0616
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.2246 ± 0.0568
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.5803 ± 0.0024
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9853 ± 0.0192
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3724 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3757 ± 0.0113
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0087 ± 0.0302
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.22 ± 0.0567
Cross-validation details (10-fold Crossvalidation)