Run
10591738

Run 10591738

Task 3954 (Supervised Classification) MagicTelescope Uploaded 24-11-2022 by Gaurav Kumar
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Flow

sklearn.ensemble._forest.RandomForestClassifier(10)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(10)_bootstraptrue
sklearn.ensemble._forest.RandomForestClassifier(10)_ccp_alpha0.0
sklearn.ensemble._forest.RandomForestClassifier(10)_class_weightnull
sklearn.ensemble._forest.RandomForestClassifier(10)_criterion"gini"
sklearn.ensemble._forest.RandomForestClassifier(10)_max_depthnull
sklearn.ensemble._forest.RandomForestClassifier(10)_max_features"auto"
sklearn.ensemble._forest.RandomForestClassifier(10)_max_leaf_nodesnull
sklearn.ensemble._forest.RandomForestClassifier(10)_max_samplesnull
sklearn.ensemble._forest.RandomForestClassifier(10)_min_impurity_decrease0.0
sklearn.ensemble._forest.RandomForestClassifier(10)_min_impurity_splitnull
sklearn.ensemble._forest.RandomForestClassifier(10)_min_samples_leaf1
sklearn.ensemble._forest.RandomForestClassifier(10)_min_samples_split2
sklearn.ensemble._forest.RandomForestClassifier(10)_min_weight_fraction_leaf0.0
sklearn.ensemble._forest.RandomForestClassifier(10)_n_estimators100
sklearn.ensemble._forest.RandomForestClassifier(10)_n_jobsnull
sklearn.ensemble._forest.RandomForestClassifier(10)_oob_scorefalse
sklearn.ensemble._forest.RandomForestClassifier(10)_random_state46674
sklearn.ensemble._forest.RandomForestClassifier(10)_verbose0
sklearn.ensemble._forest.RandomForestClassifier(10)_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

0.9369 ± 0.0058
Per class
Cross-validation details (10-fold Crossvalidation)
0.8791 ± 0.0065
Per class
Cross-validation details (10-fold Crossvalidation)
0.7317 ± 0.0147
Cross-validation details (10-fold Crossvalidation)
0.5973 ± 0.0086
Cross-validation details (10-fold Crossvalidation)
0.1944 ± 0.0035
Cross-validation details (10-fold Crossvalidation)
0.456 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.881 ± 0.0063
Cross-validation details (10-fold Crossvalidation)
19020
Per class
Cross-validation details (10-fold Crossvalidation)
0.8807 ± 0.0064
Per class
Cross-validation details (10-fold Crossvalidation)
0.881 ± 0.0063
Cross-validation details (10-fold Crossvalidation)
0.9355 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.4263 ± 0.0078
Cross-validation details (10-fold Crossvalidation)
0.4775 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.2988 ± 0.0055
Cross-validation details (10-fold Crossvalidation)
0.6259 ± 0.0115
Cross-validation details (10-fold Crossvalidation)
0.8557 ± 0.0082
Cross-validation details (10-fold Crossvalidation)