Answer: Statements I, II and III.

## Explanation **Correct Answer: D (Statements I, II and III)** **Statement I is correct:** With CART (Classification and Regression Trees), there is no need to specify an initial hyperparameter like K (number of neighbors) as required in KNN. CART automatically determines the optimal splits based on the data. **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 determine nearest neighbors. **Statement III is correct:** CART provides a visual, interpretable decision tree structure that clearly explains how predictions are made, showing the decision rules at each node. This transparency is a significant advantage over KNN's black-box nature. All three statements accurately describe advantages of CART over KNN, making option D the correct choice.

Author: LeetQuiz Editorial Team