Topic overview
Classification & Regression Trees
Tree-based models for classification and prediction — from intuition to pruning to evaluation.
Learning objectives
- •Explain how decision trees partition data using recursive splitting.
- •Distinguish between classification trees and regression trees.
- •Build, visualize, and prune a tree in R.
- •Evaluate classification trees using confusion matrix, lift, and ROC.
- •Evaluate regression trees using MAE and MSE.
- •Score new observations using a trained tree model.