Run
10560792

Run 10560792

Task 39 (Supervised Classification) sonar Uploaded 01-09-2021 by Victorien Fandos
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Flow

sklearn.ensemble._forest.RandomForestClassifier(11)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(11)_bootstrapfalse
sklearn.ensemble._forest.RandomForestClassifier(11)_ccp_alpha0.0
sklearn.ensemble._forest.RandomForestClassifier(11)_class_weightnull
sklearn.ensemble._forest.RandomForestClassifier(11)_criterion"entropy"
sklearn.ensemble._forest.RandomForestClassifier(11)_max_depth105
sklearn.ensemble._forest.RandomForestClassifier(11)_max_features"sqrt"
sklearn.ensemble._forest.RandomForestClassifier(11)_max_leaf_nodesnull
sklearn.ensemble._forest.RandomForestClassifier(11)_max_samplesnull
sklearn.ensemble._forest.RandomForestClassifier(11)_min_impurity_decrease0.0
sklearn.ensemble._forest.RandomForestClassifier(11)_min_impurity_splitnull
sklearn.ensemble._forest.RandomForestClassifier(11)_min_samples_leaf2
sklearn.ensemble._forest.RandomForestClassifier(11)_min_samples_split2
sklearn.ensemble._forest.RandomForestClassifier(11)_min_weight_fraction_leaf0.0
sklearn.ensemble._forest.RandomForestClassifier(11)_n_estimators1242
sklearn.ensemble._forest.RandomForestClassifier(11)_n_jobsnull
sklearn.ensemble._forest.RandomForestClassifier(11)_oob_scorefalse
sklearn.ensemble._forest.RandomForestClassifier(11)_random_state37710
sklearn.ensemble._forest.RandomForestClassifier(11)_verbose0
sklearn.ensemble._forest.RandomForestClassifier(11)_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

0.9472 ± 0.0266
Per class
Cross-validation details (10-fold Crossvalidation)
0.8599 ± 0.052
Per class
Cross-validation details (10-fold Crossvalidation)
0.7182 ± 0.0987
Cross-validation details (10-fold Crossvalidation)
0.472 ± 0.0529
Cross-validation details (10-fold Crossvalidation)
0.2841 ± 0.0267
Cross-validation details (10-fold Crossvalidation)
0.4978 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
0.8606 ± 0.0476
Cross-validation details (10-fold Crossvalidation)
208
Per class
Cross-validation details (10-fold Crossvalidation)
0.8625 ± 0.0362
Per class
Cross-validation details (10-fold Crossvalidation)
0.8606 ± 0.0476
Cross-validation details (10-fold Crossvalidation)
0.9967 ± 0.0033
Cross-validation details (10-fold Crossvalidation)
0.5707 ± 0.0533
Cross-validation details (10-fold Crossvalidation)
0.4989 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
0.3379 ± 0.0242
Cross-validation details (10-fold Crossvalidation)
0.6774 ± 0.0482
Cross-validation details (10-fold Crossvalidation)
0.857 ± 0.0529
Cross-validation details (10-fold Crossvalidation)