Decision Trees
Estimated time: 3 hours
Read Chapter 6: Decision Trees from Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow.
Focus on understanding:
- how a decision tree makes predictions;
- how trees split the feature space;
- why decision trees can overfit;
- how important hyperparameters control the complexity of a tree.
Use the three-pass method.
First Pass: Get the Big Picture — 30 minutes
- Skim the section titles.
- Look at the plots and figures.
- Read exercise questions 1–6.
Goal: Understand the structure of the chapter and the main ideas behind decision trees.
Second Pass: Read for Understanding — 2 hours
Read the chapter carefully.
Focus on how decision trees are constructed, how they make predictions, and how their behaviour can be controlled.
Goal: Develop a conceptual understanding of decision trees and their main strengths and limitations.
Third Pass: Review — 30 minutes
Answer exercise questions 1–6.
Return to the relevant sections whenever you are unsure about an answer.
Goal: Check whether you can explain the important concepts without relying on the text.