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.