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Jul 18th, 2023
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Python 0.35 KB | Source Code | 0 0
  1. from sklearn.ensemble import RandomForestClassifier
  2. from sklearn.datasets import make_classification
  3.  
  4. X, y = make_classification(n_samples=1000, n_features=4,
  5.                            n_informative=2, n_redundant=0,
  6.                            random_state=0, shuffle=False)
  7. clf = RandomForestClassifier(n_estimators=100, random_state=0)
  8. clf.fit(X, y)
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