Decision Trees

Twenty questions with data

An interactive lesson with 6 steps, about 5 minutes: you predict, drag and solve, with instant feedback on every answer. It runs in your browser and needs JavaScript.

What you’ll learn

• A decision tree classifies with a sequence of threshold questions.
• Splits are chosen to minimise weighted Gini impurity.
• Deep trees overfit; forests of trees vote to reduce it.

Steps

1. A flowchart of questions
2. The first question
3. Growing deeper
4. Gini impurity
5. Scoring a split
6. Forests