I am not able to achieve the desired result when I use the .estimators_ attribute from DecisionTreeRegressor in ways similar to the example in Lesson 9.
I am tying to display a graph of out-of-bag error versus .nestimators_ with this line of code:
preds = np.stack([t.predict(valid_xs) for t in m.estimators_])
But, instead of displaying the graph, the following line of code is printed repeatedly:
/usr/local/lib/python3.7/dist-packages/sklearn/base.py:444: UserWarning: X has feature names, but DecisionTreeRegressor was fitted without feature names
f"X has feature names, but {self.__class__.__name__} was fitted without"
Any help interpreting this and solving the issue I am having would be appreciated.
-Simon