Chapter 14: Classification

Predict categories with supervised learning and evaluate classifier accuracy.

Learning Goals

• Use labeled examples for category prediction.
• Explain nearest-neighbor classification.
• Evaluate classifiers with train/test data and accuracy.

Chapter Flow

• Classification foundations
• Nearest neighbors
• Training, testing, and accuracy
• Rows of tables
• Implementing the classifier

What To Watch For

• The main concept introduced in each section
• The code pattern that supports the concept
• The management question the method helps answer

Carry Forward

• Use the section practice exercises to check runnable code skills.
• Keep the notebook examples runnable.
• Connect each method to interpretation, not just syntax.
• Use the glossary terms when explaining results.