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Dec 15th, 2018
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  1. from sklearn.ensemble import BaggingClassifier
  2. from sklearn.tree import DecisionTreeClassifier
  3.  
  4. clf = BaggingClassifier(base_estimator=DecisionTreeClassifier(), max_samples=0.5)
  5.  
  6. def set_rf_samples(n):
  7. """ Changes Scikit learn's random forests to give each tree a random sample of
  8. n random rows.
  9. """
  10. forest._generate_sample_indices = (lambda rs, n_samples:
  11. forest.check_random_state(rs).randint(0, n_samples, n))
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