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sklearn random forest regressor Code Example
sklearn random forest regressor 
from sklearn.ensemble import RandomForestRegressor


clf = RandomForestRegressor(max_depth=2, random_state=0)

clf.fit(X, y)

print(clf.predict([[0, 0, 0, 0]]))
how to use random tree in python 
from sklearn.model_selection import train_test_split

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)
Source: stackabuse.com
sklearn random forest 
from sklearn.ensemble import RandomForestClassifier
from sklearn.datasets import make_classification


X, y = make_classification(n_samples=1000, n_features=4,
                            n_informative=2, n_redundant=0,
                            random_state=0, shuffle=False)
clf = RandomForestClassifier(max_depth=2, random_state=0)

clf.fit(X, y)

print(clf.predict([[0, 0, 0, 0]]))



Python

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Category:
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Sub Category:
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