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- from sklearn.ensemble import BaggingClassifier
- from sklearn.tree import DecisionTreeClassifier
- clf = BaggingClassifier(base_estimator=DecisionTreeClassifier(), max_samples=0.5)
- def set_rf_samples(n):
- """ Changes Scikit learn's random forests to give each tree a random sample of
- n random rows.
- """
- forest._generate_sample_indices = (lambda rs, n_samples:
- forest.check_random_state(rs).randint(0, n_samples, n))
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