Cross-Validation Score

Task

Use 5-fold cross-validation to evaluate a Random Forest classifier on the digits dataset.

Why It Matters

A single train/test split can give misleading results depending on how the data happens to be divided. Cross-validation provides a more robust estimate by training and testing on multiple different splits, giving you both a mean score and variance.

Instructions

1. Examine the setup code and data
2. Modify the code to solve the puzzle
3. Click Run or press Ctrl+Enter to execute