Using sklearn, how do I find depth of a decision tree?

Question

I am training a decision tree with sklearn. When I use:

dt_clf = tree.DecisionTreeClassifier()

the max_depth parameter defaults to None. According to the documentation, if max_depth is None, then nodes are expanded until all leaves are pure or until all leaves contain less than min_samples_split samples.

After fitting my model, how do I find out what max_depth actually is? The get_params() function doesn't help. After fitting, get_params() it still says None.

How can I get the actual number for max_depth?

Docs: https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html

Answer 1

The answer according to the docs https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html#sklearn.tree.DecisionTreeClassifier.get_depth is to use the tree.get_depth() function.