Run
3471

Run 3471

Task 115 (Supervised Classification) diabetes Uploaded 01-03-2021 by Test Test
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  • openml-python Sklearn_0.23.1. study_464
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Flow

sklearn.ensemble._forest.RandomForestClassifier(2)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(2)_bootstraptrue
sklearn.ensemble._forest.RandomForestClassifier(2)_ccp_alpha0.0
sklearn.ensemble._forest.RandomForestClassifier(2)_class_weightnull
sklearn.ensemble._forest.RandomForestClassifier(2)_criterion"gini"
sklearn.ensemble._forest.RandomForestClassifier(2)_max_depthnull
sklearn.ensemble._forest.RandomForestClassifier(2)_max_features"auto"
sklearn.ensemble._forest.RandomForestClassifier(2)_max_leaf_nodesnull
sklearn.ensemble._forest.RandomForestClassifier(2)_max_samplesnull
sklearn.ensemble._forest.RandomForestClassifier(2)_min_impurity_decrease0.0
sklearn.ensemble._forest.RandomForestClassifier(2)_min_impurity_splitnull
sklearn.ensemble._forest.RandomForestClassifier(2)_min_samples_leaf1
sklearn.ensemble._forest.RandomForestClassifier(2)_min_samples_split2
sklearn.ensemble._forest.RandomForestClassifier(2)_min_weight_fraction_leaf0.0
sklearn.ensemble._forest.RandomForestClassifier(2)_n_estimators100
sklearn.ensemble._forest.RandomForestClassifier(2)_n_jobsnull
sklearn.ensemble._forest.RandomForestClassifier(2)_oob_scorefalse
sklearn.ensemble._forest.RandomForestClassifier(2)_random_state56882
sklearn.ensemble._forest.RandomForestClassifier(2)_verbose0
sklearn.ensemble._forest.RandomForestClassifier(2)_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

0.8298 ± 0.0426
Per class
Cross-validation details (10-fold Crossvalidation)
0.7705 ± 0.0593
Per class
Cross-validation details (10-fold Crossvalidation)
0.4867 ± 0.1326
Cross-validation details (10-fold Crossvalidation)
0.3122 ± 0.0618
Cross-validation details (10-fold Crossvalidation)
0.3181 ± 0.0234
Cross-validation details (10-fold Crossvalidation)
0.4545 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
0.776 ± 0.0578
Cross-validation details (10-fold Crossvalidation)
768
Per class
Cross-validation details (10-fold Crossvalidation)
0.771 ± 0.0612
Per class
Cross-validation details (10-fold Crossvalidation)
0.776 ± 0.0578
Cross-validation details (10-fold Crossvalidation)
0.9331 ± 0.0032
Cross-validation details (10-fold Crossvalidation)
0.6999 ± 0.0518
Cross-validation details (10-fold Crossvalidation)
0.4766 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
0.3979 ± 0.0258
Cross-validation details (10-fold Crossvalidation)
0.8349 ± 0.0548
Cross-validation details (10-fold Crossvalidation)
0.7336 ± 0.0636
Cross-validation details (10-fold Crossvalidation)