Problem 2: Compare Train vs Test Error for an Overly Complex Model

Problem Description

Write a Python program that trains a very deep Decision Tree (max_depth=20 or no limit) on the same dataset, and compares its training and test error, to observe signs of high variance.

Input

The same dataset split into training and test sets.

Output

Training and test MSE for the deep model.

Constraints

• Use the same dataset as Problem 1 for direct comparison.

Example Input

text
(The same dataset as Problem 1)

Example Output

text
Train MSE: 0.002
Test MSE: 0.19

Concepts Covered

DecisionTreeRegressor, max_depth, overfitting diagnosis.