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  3. Machine Learning with Tree-Based Models in Python

Exercise

Instantiate the model

In the following set of exercises, you'll diagnose the bias and variance problems of a regression tree. The regression tree you'll define in this exercise will be used to predict the mpg consumption of cars from the auto dataset using all available features.

We have already processed the data and loaded the features matrix X and the array y in your workspace. In addition, the DecisionTreeRegressor class was imported from sklearn.tree.

Instructions

100 XP
  • Import train_test_split from sklearn.model_selection.
  • Split the data into 70% train and 30% test.
  • Instantiate a DecisionTreeRegressor with max depth 4 and min_samples_leaf set to 0.26.