Answer: Statements I, II and III.

## Explanation **Statement I is correct**: CART does not require specifying an initial hyperparameter like K in KNN. While CART has parameters like tree depth, it doesn't have a mandatory hyperparameter equivalent to K. **Statement II is correct**: CART does not require specifying a similarity or distance measure, unlike KNN which relies on distance metrics (Euclidean, Manhattan, etc.) to find nearest neighbors. **Statement III is correct**: CART provides a visual explanation through its tree structure, making it interpretable and allowing users to understand the decision path, while KNN is more of a "black box" approach. All three statements accurately describe advantages of CART over KNN.

Author: LeetQuiz .