Chapter 6: Decision Trees: Introduction
Details: Simple Prediction Illustration
Demo 6.1: Building a Decision Tree Model with Default Settings
Pros and Cons of Decision Trees
Introduction
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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