I was analyzing the classifier created using a decision tree. There is a tuning parameter called max_depth in scikit's decision tree. Is this equivalent of pruning a decision tree? If not, how could I prune a decision tree using scikit?
dt_ap = tree.DecisionTreeClassifier(random_state=1, max_depth=13) boosted_dt = AdaBoostClassifier(dt_ap, random_state=1) boosted_dt.fit(X_train, Y_train)