Run
10591883

Run 10591883

Task 3954 (Supervised Classification) MagicTelescope Uploaded 10-03-2023 by Artur Dev
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Flow

sklearn.ensemble._forest.RandomForestClassifier(25)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(25)_bootstraptrue
sklearn.ensemble._forest.RandomForestClassifier(25)_ccp_alpha0.0
sklearn.ensemble._forest.RandomForestClassifier(25)_class_weightnull
sklearn.ensemble._forest.RandomForestClassifier(25)_criterion"gini"
sklearn.ensemble._forest.RandomForestClassifier(25)_max_depthnull
sklearn.ensemble._forest.RandomForestClassifier(25)_max_features"auto"
sklearn.ensemble._forest.RandomForestClassifier(25)_max_leaf_nodesnull
sklearn.ensemble._forest.RandomForestClassifier(25)_max_samplesnull
sklearn.ensemble._forest.RandomForestClassifier(25)_min_impurity_decrease0.0
sklearn.ensemble._forest.RandomForestClassifier(25)_min_samples_leaf1
sklearn.ensemble._forest.RandomForestClassifier(25)_min_samples_split2
sklearn.ensemble._forest.RandomForestClassifier(25)_min_weight_fraction_leaf0.0
sklearn.ensemble._forest.RandomForestClassifier(25)_n_estimators100
sklearn.ensemble._forest.RandomForestClassifier(25)_n_jobsnull
sklearn.ensemble._forest.RandomForestClassifier(25)_oob_scorefalse
sklearn.ensemble._forest.RandomForestClassifier(25)_random_state32698
sklearn.ensemble._forest.RandomForestClassifier(25)_verbose0
sklearn.ensemble._forest.RandomForestClassifier(25)_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

0.9368 ± 0.0052
Per class
Cross-validation details (10-fold Crossvalidation)
0.8797 ± 0.0056
Per class
Cross-validation details (10-fold Crossvalidation)
0.733 ± 0.0127
Cross-validation details (10-fold Crossvalidation)
0.5975 ± 0.0083
Cross-validation details (10-fold Crossvalidation)
0.1942 ± 0.0033
Cross-validation details (10-fold Crossvalidation)
0.456 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.8816 ± 0.0053
Cross-validation details (10-fold Crossvalidation)
19020
Per class
Cross-validation details (10-fold Crossvalidation)
0.8813 ± 0.0054
Per class
Cross-validation details (10-fold Crossvalidation)
0.8816 ± 0.0053
Cross-validation details (10-fold Crossvalidation)
0.9355 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.426 ± 0.0072
Cross-validation details (10-fold Crossvalidation)
0.4775 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.2989 ± 0.0052
Cross-validation details (10-fold Crossvalidation)
0.626 ± 0.0109
Cross-validation details (10-fold Crossvalidation)
0.8564 ± 0.0075
Cross-validation details (10-fold Crossvalidation)