How to use 'randomforestregressor' in Python

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qiriro/PPG

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

jianhaod/Kaggle

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

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

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

How to use 'randomforestregressor' in Python

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