Run
10593658

Run 10593658

Task 3954 (Supervised Classification) MagicTelescope Uploaded 29-04-2023 by Jaime Ferreira
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Flow

sklearn.ensemble._forest.RandomForestClassifier(28)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(28)_bootstraptrue
sklearn.ensemble._forest.RandomForestClassifier(28)_ccp_alpha0.0
sklearn.ensemble._forest.RandomForestClassifier(28)_class_weightnull
sklearn.ensemble._forest.RandomForestClassifier(28)_criterion"gini"
sklearn.ensemble._forest.RandomForestClassifier(28)_max_depthnull
sklearn.ensemble._forest.RandomForestClassifier(28)_max_features"sqrt"
sklearn.ensemble._forest.RandomForestClassifier(28)_max_leaf_nodesnull
sklearn.ensemble._forest.RandomForestClassifier(28)_max_samplesnull
sklearn.ensemble._forest.RandomForestClassifier(28)_min_impurity_decrease0.0
sklearn.ensemble._forest.RandomForestClassifier(28)_min_samples_leaf1
sklearn.ensemble._forest.RandomForestClassifier(28)_min_samples_split2
sklearn.ensemble._forest.RandomForestClassifier(28)_min_weight_fraction_leaf0.0
sklearn.ensemble._forest.RandomForestClassifier(28)_n_estimators100
sklearn.ensemble._forest.RandomForestClassifier(28)_n_jobsnull
sklearn.ensemble._forest.RandomForestClassifier(28)_oob_scorefalse
sklearn.ensemble._forest.RandomForestClassifier(28)_random_state7870
sklearn.ensemble._forest.RandomForestClassifier(28)_verbose0
sklearn.ensemble._forest.RandomForestClassifier(28)_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

0.9366 ± 0.0059
Per class
Cross-validation details (10-fold Crossvalidation)
0.8807 ± 0.0071
Per class
Cross-validation details (10-fold Crossvalidation)
0.735 ± 0.016
Cross-validation details (10-fold Crossvalidation)
0.5986 ± 0.0096
Cross-validation details (10-fold Crossvalidation)
0.1938 ± 0.0038
Cross-validation details (10-fold Crossvalidation)
0.456 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.8827 ± 0.0067
Cross-validation details (10-fold Crossvalidation)
19020
Per class
Cross-validation details (10-fold Crossvalidation)
0.8826 ± 0.0066
Per class
Cross-validation details (10-fold Crossvalidation)
0.8827 ± 0.0067
Cross-validation details (10-fold Crossvalidation)
0.9355 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.425 ± 0.0084
Cross-validation details (10-fold Crossvalidation)
0.4775 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.2987 ± 0.0059
Cross-validation details (10-fold Crossvalidation)
0.6255 ± 0.0123
Cross-validation details (10-fold Crossvalidation)
0.8568 ± 0.0094
Cross-validation details (10-fold Crossvalidation)