Run
10593656

Run 10593656

Task 3954 (Supervised Classification) MagicTelescope Uploaded 25-04-2023 by Juan Alvarez
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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_state55374
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

0.9362 ± 0.0058
Per class
Cross-validation details (10-fold Crossvalidation)
0.8793 ± 0.0077
Per class
Cross-validation details (10-fold Crossvalidation)
0.7322 ± 0.0174
Cross-validation details (10-fold Crossvalidation)
0.597 ± 0.01
Cross-validation details (10-fold Crossvalidation)
0.1943 ± 0.0041
Cross-validation details (10-fold Crossvalidation)
0.456 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.8812 ± 0.0074
Cross-validation details (10-fold Crossvalidation)
19020
Per class
Cross-validation details (10-fold Crossvalidation)
0.8809 ± 0.0075
Per class
Cross-validation details (10-fold Crossvalidation)
0.8812 ± 0.0074
Cross-validation details (10-fold Crossvalidation)
0.9355 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.426 ± 0.0089
Cross-validation details (10-fold Crossvalidation)
0.4775 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.2996 ± 0.0061
Cross-validation details (10-fold Crossvalidation)
0.6275 ± 0.0128
Cross-validation details (10-fold Crossvalidation)
0.856 ± 0.0096
Cross-validation details (10-fold Crossvalidation)