OpenML
10594070

Run 10594070

Task 3954 (Supervised Classification) MagicTelescope Uploaded 28-11-2023 by José M. Sánchez
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Flow

sklearn.ensemble._forest.RandomForestClassifier(37)A random forest classifier. A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and uses averaging to improve the predictive accuracy and control over-fitting. The sub-sample size is controlled with the `max_samples` parameter if `bootstrap=True` (default), otherwise the whole dataset is used to build each tree.
sklearn.ensemble._forest.RandomForestClassifier(37)_bootstraptrue
sklearn.ensemble._forest.RandomForestClassifier(37)_ccp_alpha0.0
sklearn.ensemble._forest.RandomForestClassifier(37)_class_weightnull
sklearn.ensemble._forest.RandomForestClassifier(37)_criterion"gini"
sklearn.ensemble._forest.RandomForestClassifier(37)_max_depthnull
sklearn.ensemble._forest.RandomForestClassifier(37)_max_features"sqrt"
sklearn.ensemble._forest.RandomForestClassifier(37)_max_leaf_nodesnull
sklearn.ensemble._forest.RandomForestClassifier(37)_max_samplesnull
sklearn.ensemble._forest.RandomForestClassifier(37)_min_impurity_decrease0.0
sklearn.ensemble._forest.RandomForestClassifier(37)_min_samples_leaf1
sklearn.ensemble._forest.RandomForestClassifier(37)_min_samples_split2
sklearn.ensemble._forest.RandomForestClassifier(37)_min_weight_fraction_leaf0.0
sklearn.ensemble._forest.RandomForestClassifier(37)_n_estimators100
sklearn.ensemble._forest.RandomForestClassifier(37)_n_jobsnull
sklearn.ensemble._forest.RandomForestClassifier(37)_oob_scorefalse
sklearn.ensemble._forest.RandomForestClassifier(37)_random_state2311
sklearn.ensemble._forest.RandomForestClassifier(37)_verbose0
sklearn.ensemble._forest.RandomForestClassifier(37)_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.

18 Evaluation measures

0.9367 ± 0.0059
Per class
Cross-validation details (10-fold Crossvalidation)
0.8795 ± 0.0072
Per class
Cross-validation details (10-fold Crossvalidation)
0.7325 ± 0.0163
Cross-validation details (10-fold Crossvalidation)
0.5969 ± 0.0091
Cross-validation details (10-fold Crossvalidation)
0.1944 ± 0.0035
Cross-validation details (10-fold Crossvalidation)
0.456 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.8814 ± 0.0068
Cross-validation details (10-fold Crossvalidation)
19020
Per class
Cross-validation details (10-fold Crossvalidation)
0.8812 ± 0.0068
Per class
Cross-validation details (10-fold Crossvalidation)
0.8814 ± 0.0068
Cross-validation details (10-fold Crossvalidation)
0.9355 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.4263 ± 0.0078
Cross-validation details (10-fold Crossvalidation)
0.4775 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.2993 ± 0.0058
Cross-validation details (10-fold Crossvalidation)
0.6268 ± 0.0122
Cross-validation details (10-fold Crossvalidation)
0.8559 ± 0.0094
Cross-validation details (10-fold Crossvalidation)