Run
10593650

Run 10593650

Task 3954 (Supervised Classification) MagicTelescope Uploaded 19-04-2023 by Juheon Kwak
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Flow

sklearn.ensemble._forest.RandomForestClassifier(29)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(29)_bootstraptrue
sklearn.ensemble._forest.RandomForestClassifier(29)_ccp_alpha0.0
sklearn.ensemble._forest.RandomForestClassifier(29)_class_weightnull
sklearn.ensemble._forest.RandomForestClassifier(29)_criterion"gini"
sklearn.ensemble._forest.RandomForestClassifier(29)_max_depthnull
sklearn.ensemble._forest.RandomForestClassifier(29)_max_features"auto"
sklearn.ensemble._forest.RandomForestClassifier(29)_max_leaf_nodesnull
sklearn.ensemble._forest.RandomForestClassifier(29)_max_samplesnull
sklearn.ensemble._forest.RandomForestClassifier(29)_min_impurity_decrease0.0
sklearn.ensemble._forest.RandomForestClassifier(29)_min_samples_leaf1
sklearn.ensemble._forest.RandomForestClassifier(29)_min_samples_split2
sklearn.ensemble._forest.RandomForestClassifier(29)_min_weight_fraction_leaf0.0
sklearn.ensemble._forest.RandomForestClassifier(29)_n_estimators100
sklearn.ensemble._forest.RandomForestClassifier(29)_n_jobsnull
sklearn.ensemble._forest.RandomForestClassifier(29)_oob_scorefalse
sklearn.ensemble._forest.RandomForestClassifier(29)_random_state31362
sklearn.ensemble._forest.RandomForestClassifier(29)_verbose0
sklearn.ensemble._forest.RandomForestClassifier(29)_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 ± 0.0062
Per class
Cross-validation details (10-fold Crossvalidation)
0.8794 ± 0.0071
Per class
Cross-validation details (10-fold Crossvalidation)
0.7324 ± 0.0161
Cross-validation details (10-fold Crossvalidation)
0.5969 ± 0.0101
Cross-validation details (10-fold Crossvalidation)
0.1944 ± 0.0041
Cross-validation details (10-fold Crossvalidation)
0.456 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.8814 ± 0.0067
Cross-validation details (10-fold Crossvalidation)
19020
Per class
Cross-validation details (10-fold Crossvalidation)
0.8812 ± 0.0067
Per class
Cross-validation details (10-fold Crossvalidation)
0.8814 ± 0.0067
Cross-validation details (10-fold Crossvalidation)
0.9355 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.4264 ± 0.0089
Cross-validation details (10-fold Crossvalidation)
0.4775 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.2995 ± 0.0062
Cross-validation details (10-fold Crossvalidation)
0.6273 ± 0.013
Cross-validation details (10-fold Crossvalidation)
0.8559 ± 0.0094
Cross-validation details (10-fold Crossvalidation)