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Task 119 (Supervised Classification) diabetes Uploaded 11-01-2024 by Continuous Integration
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sklearn.ensemble._forest.RandomForestClassifier(5)	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(5)_bootstrap	true
sklearn.ensemble._forest.RandomForestClassifier(5)_ccp_alpha	0.0
sklearn.ensemble._forest.RandomForestClassifier(5)_class_weight	null
sklearn.ensemble._forest.RandomForestClassifier(5)_criterion	"gini"
sklearn.ensemble._forest.RandomForestClassifier(5)_max_depth	null
sklearn.ensemble._forest.RandomForestClassifier(5)_max_features	"auto"
sklearn.ensemble._forest.RandomForestClassifier(5)_max_leaf_nodes	null
sklearn.ensemble._forest.RandomForestClassifier(5)_max_samples	null
sklearn.ensemble._forest.RandomForestClassifier(5)_min_impurity_decrease	0.0
sklearn.ensemble._forest.RandomForestClassifier(5)_min_impurity_split	null
sklearn.ensemble._forest.RandomForestClassifier(5)_min_samples_leaf	1
sklearn.ensemble._forest.RandomForestClassifier(5)_min_samples_split	2
sklearn.ensemble._forest.RandomForestClassifier(5)_min_weight_fraction_leaf	0.0
sklearn.ensemble._forest.RandomForestClassifier(5)_n_estimators	33
sklearn.ensemble._forest.RandomForestClassifier(5)_n_jobs	null
sklearn.ensemble._forest.RandomForestClassifier(5)_oob_score	false
sklearn.ensemble._forest.RandomForestClassifier(5)_random_state	42870
sklearn.ensemble._forest.RandomForestClassifier(5)_verbose	0
sklearn.ensemble._forest.RandomForestClassifier(5)_warm_start	false