OpenML
10594081

Run 10594081

Task 3954 (Supervised Classification) MagicTelescope Uploaded 05-01-2024 by Sy Tuan NGUYEN
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Flow

sklearn.ensemble._forest.RandomForestClassifier(32)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(32)_bootstraptrue
sklearn.ensemble._forest.RandomForestClassifier(32)_ccp_alpha0.0
sklearn.ensemble._forest.RandomForestClassifier(32)_class_weightnull
sklearn.ensemble._forest.RandomForestClassifier(32)_criterion"gini"
sklearn.ensemble._forest.RandomForestClassifier(32)_max_depthnull
sklearn.ensemble._forest.RandomForestClassifier(32)_max_features"sqrt"
sklearn.ensemble._forest.RandomForestClassifier(32)_max_leaf_nodesnull
sklearn.ensemble._forest.RandomForestClassifier(32)_max_samplesnull
sklearn.ensemble._forest.RandomForestClassifier(32)_min_impurity_decrease0.0
sklearn.ensemble._forest.RandomForestClassifier(32)_min_samples_leaf1
sklearn.ensemble._forest.RandomForestClassifier(32)_min_samples_split2
sklearn.ensemble._forest.RandomForestClassifier(32)_min_weight_fraction_leaf0.0
sklearn.ensemble._forest.RandomForestClassifier(32)_n_estimators100
sklearn.ensemble._forest.RandomForestClassifier(32)_n_jobsnull
sklearn.ensemble._forest.RandomForestClassifier(32)_oob_scorefalse
sklearn.ensemble._forest.RandomForestClassifier(32)_random_state1102
sklearn.ensemble._forest.RandomForestClassifier(32)_verbose0
sklearn.ensemble._forest.RandomForestClassifier(32)_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 ± 0.0061
Per class
Cross-validation details (10-fold Crossvalidation)
0.8803 ± 0.0077
Per class
Cross-validation details (10-fold Crossvalidation)
0.7345 ± 0.0173
Cross-validation details (10-fold Crossvalidation)
0.5974 ± 0.01
Cross-validation details (10-fold Crossvalidation)
0.1943 ± 0.004
Cross-validation details (10-fold Crossvalidation)
0.456 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.8822 ± 0.0073
Cross-validation details (10-fold Crossvalidation)
19020
Per class
Cross-validation details (10-fold Crossvalidation)
0.8819 ± 0.0074
Per class
Cross-validation details (10-fold Crossvalidation)
0.8822 ± 0.0073
Cross-validation details (10-fold Crossvalidation)
0.9355 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.4261 ± 0.0088
Cross-validation details (10-fold Crossvalidation)
0.4775 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.299 ± 0.0061
Cross-validation details (10-fold Crossvalidation)
0.6261 ± 0.0127
Cross-validation details (10-fold Crossvalidation)
0.8572 ± 0.0097
Cross-validation details (10-fold Crossvalidation)