Run 10587761

Task 119 (Learning Curve) zoo Uploaded 17-04-2022 by Tan Tran
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sklearn.ensemble._forest.RandomForestClassifier(13)	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(13)_bootstrap	true
sklearn.ensemble._forest.RandomForestClassifier(13)_ccp_alpha	0.0
sklearn.ensemble._forest.RandomForestClassifier(13)_class_weight	null
sklearn.ensemble._forest.RandomForestClassifier(13)_criterion	"gini"
sklearn.ensemble._forest.RandomForestClassifier(13)_max_depth	null
sklearn.ensemble._forest.RandomForestClassifier(13)_max_features	"auto"
sklearn.ensemble._forest.RandomForestClassifier(13)_max_leaf_nodes	null
sklearn.ensemble._forest.RandomForestClassifier(13)_max_samples	null
sklearn.ensemble._forest.RandomForestClassifier(13)_min_impurity_decrease	0.0
sklearn.ensemble._forest.RandomForestClassifier(13)_min_samples_leaf	1
sklearn.ensemble._forest.RandomForestClassifier(13)_min_samples_split	2
sklearn.ensemble._forest.RandomForestClassifier(13)_min_weight_fraction_leaf	0.0
sklearn.ensemble._forest.RandomForestClassifier(13)_n_estimators	100
sklearn.ensemble._forest.RandomForestClassifier(13)_n_jobs	null
sklearn.ensemble._forest.RandomForestClassifier(13)_oob_score	false
sklearn.ensemble._forest.RandomForestClassifier(13)_random_state	7542
sklearn.ensemble._forest.RandomForestClassifier(13)_verbose	0
sklearn.ensemble._forest.RandomForestClassifier(13)_warm_start	false