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75 def random_forest_classifier(features, labels): 76 parameters = { 77 'n_estimators': range(10, 201, 10), 78 'max_depth': [None] + range(1, 11, 1), 79 } 80 classifier = GridSearchCV(RandomForestClassifier(random_state=1), parameters, n_jobs=-1) 81 classifier.fit(features, labels) 82 return classifier
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52 def randomforestClassifier(trainData, trainLabel): 53 54 rfClf = RandomForestClassifier(n_estimators=110, max_depth=5, min_samples_split=2, 55 min_samples_leaf=1,random_state=34) 56 rfClf.fit(trainData, trainLabel) 57 return rfClf