18687 sklearn==0.23.2 numpy>=1.6.1 scipy>=0.9 openml==0.10.2,sklearn==0.23.2 5 public 0 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. 2020-01-24T23:48:34Z sklearn.ensemble._forest.RandomForestClassifier 0 sklearn.ensemble._forest.RandomForestClassifier 0