Lab 09 · Quiz
Decision Trees Quiz
Recursive splitting
Entropy
Information gain
Pruning
Work in progress This quiz is still being reviewed: questions may change, and some parts may still contain mistakes.
Before you start
Quiz for Lab 09: Decision Trees. Answer every task, then press Check answers at the bottom: each answer is marked, the explanations appear, and you get a score per skill.
Assumptions unless stated otherwise
- Lower entropy means a purer node; entropy uses \(\log_2\) and is measured in bits.
- For ID3, the split with the largest information gain is preferred.
- In classification a leaf predicts a class; in regression a leaf predicts a numeric value.
- Tree building is greedy: each split is chosen locally.
How answers are scored
- Numbers: type the value as a decimal, e.g. 0.55.
- Rows: one choice per row; each correct row earns its share of the points.
- Select all that apply: scores only when the selection is exactly right.
- Your answers are saved in this browser only, so you can leave and come back. Nothing is sent anywhere.