scikit learn random forest

from sklearn.ensemble import RandomForestClassifier


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

clf.fit(X, y)

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

Here is what the above code is Doing:
1. Creating a RandomForestClassifier object with max_depth=2 and random_state=0.
2. Fitting the classifier to the training data.
3. Predicting the label of [[0, 0, 0, 0]], which is [[0.0]].