Chapter 6: Decision Trees: Introduction


Decision Tree Algorithm

Classification Tree

Regression Tree

Building a Decision Tree

How Splits Are Chosen

How Many Questions Are Asked?

Details: Simple Prediction Illustration

Demo 6.1: Building a Decision Tree Model with Default Settings

Pros and Cons of Decision Trees





Decision trees and ensembles of trees are supervised learning algorithms that are widely used models for classification and regression tasks. In their simplest forms, decision trees learn a hierarchy of if/else questions, leading to a decision. Essentially, decision trees are statistical models designed for supervised prediction problems. Supervised prediction encompasses predictive modeling, pattern ...

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