ensemble

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ensemble.RandomForestClassifier()

class sklearn.ensemble.RandomForestClassifier(n_estimators=10, criterion='gini', max_depth=None, min_samples_split=2, min_samples_leaf=1

2017-01-15 04:21:48

ensemble.BaggingClassifier()

class sklearn.ensemble.BaggingClassifier(base_estimator=None, n_estimators=10, max_samples=1.0, max_features=1.0, bootstrap=True

2017-01-15 04:21:39

ensemble.RandomTreesEmbedding()

class sklearn.ensemble.RandomTreesEmbedding(n_estimators=10, max_depth=5, min_samples_split=2, min_samples_leaf=1, min_weight_fraction_leaf=0

2017-01-15 04:21:50

ensemble.RandomForestRegressor()

class sklearn.ensemble.RandomForestRegressor(n_estimators=10, criterion='mse', max_depth=None, min_samples_split=2, min_samples_leaf=1

2017-01-15 04:21:49

ensemble.BaggingRegressor()

class sklearn.ensemble.BaggingRegressor(base_estimator=None, n_estimators=10, max_samples=1.0, max_features=1.0, bootstrap=True,

2017-01-15 04:21:40

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