Run
10587877

Run 10587877

Task 3954 (Supervised Classification) MagicTelescope Uploaded 28-06-2022 by Allison Yang
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  • openml-python Sklearn_0.22.2.post1.
Issue #Downvotes for this reason By


Flow

sklearn.ensemble._forest.RandomForestClassifier(15)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 always the same as the original input sample size but the samples are drawn with replacement if `bootstrap=True` (default).
sklearn.ensemble._forest.RandomForestClassifier(15)_bootstraptrue
sklearn.ensemble._forest.RandomForestClassifier(15)_ccp_alpha0.0
sklearn.ensemble._forest.RandomForestClassifier(15)_class_weightnull
sklearn.ensemble._forest.RandomForestClassifier(15)_criterion"gini"
sklearn.ensemble._forest.RandomForestClassifier(15)_max_depthnull
sklearn.ensemble._forest.RandomForestClassifier(15)_max_features"auto"
sklearn.ensemble._forest.RandomForestClassifier(15)_max_leaf_nodesnull
sklearn.ensemble._forest.RandomForestClassifier(15)_max_samplesnull
sklearn.ensemble._forest.RandomForestClassifier(15)_min_impurity_decrease0.0
sklearn.ensemble._forest.RandomForestClassifier(15)_min_impurity_splitnull
sklearn.ensemble._forest.RandomForestClassifier(15)_min_samples_leaf1
sklearn.ensemble._forest.RandomForestClassifier(15)_min_samples_split2
sklearn.ensemble._forest.RandomForestClassifier(15)_min_weight_fraction_leaf0.0
sklearn.ensemble._forest.RandomForestClassifier(15)_n_estimators100
sklearn.ensemble._forest.RandomForestClassifier(15)_n_jobsnull
sklearn.ensemble._forest.RandomForestClassifier(15)_oob_scorefalse
sklearn.ensemble._forest.RandomForestClassifier(15)_random_state561
sklearn.ensemble._forest.RandomForestClassifier(15)_verbose0
sklearn.ensemble._forest.RandomForestClassifier(15)_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

0.9366 ± 0.006
Per class
Cross-validation details (10-fold Crossvalidation)
0.8791 ± 0.0066
Per class
Cross-validation details (10-fold Crossvalidation)
0.7316 ± 0.0151
Cross-validation details (10-fold Crossvalidation)
0.5975 ± 0.0096
Cross-validation details (10-fold Crossvalidation)
0.1944 ± 0.0039
Cross-validation details (10-fold Crossvalidation)
0.456 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.881 ± 0.0062
Cross-validation details (10-fold Crossvalidation)
19020
Per class
Cross-validation details (10-fold Crossvalidation)
0.8807 ± 0.006
Per class
Cross-validation details (10-fold Crossvalidation)
0.881 ± 0.0062
Cross-validation details (10-fold Crossvalidation)
0.9355 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.4263 ± 0.0085
Cross-validation details (10-fold Crossvalidation)
0.4775 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.2987 ± 0.006
Cross-validation details (10-fold Crossvalidation)
0.6255 ± 0.0126
Cross-validation details (10-fold Crossvalidation)
0.8557 ± 0.0091
Cross-validation details (10-fold Crossvalidation)