Select all correct statements regarding decision trees and their applications:

Group of answer choices

Although decision trees are simple and useful for interpretation, they are typically less accurate in prediction compared to advanced supervised learning methods, such as

ensemble techniques like random forests and boosting.

Decision trees typically use a method called recursive binary splitting to segment the predictor space into regions, which are often high$-$dimensional rectangles, boxes, and diagonal lines.