Select all correct statements regarding decision trees and their applications:

In regression trees, predictions for a given observation are made using the mean response of the

training observations within the same region.

A classification tree predicts the response by assigning the mean to the most commonly occurring

class of training observations in the region to which it belongs.

Decision trees can be applied to both regression and classification tasks. where they segment the

predictor space into a number of simple regions. Predictions for an observation are based on the mean

or mode of the responses in the region where it belongs.

Decision trees typically use a method called recursive binary splitting to segment the predictor space

into regions, which are often high$-$dimensional rectangles, bowes, and diagonal lines.

Although decision trees are simple and useful for interpretation, they are typically less accurate in

prediction compared to advanced supervised learning methods. sukh as ensemble techniques like

random forests and boosting.