Chapter 15: Clustering

Group observations without known labels and interpret whether the groups are useful.

Learning Goals

• Explain unsupervised grouping in a management context.
• Choose features and scaling choices for clustering.
• Fit k-means with centers and assignments.
• Compare k values with elbow and silhouette checks.
• Interpret cluster labels with domain judgment.

Chapter Flow

• Clustering concepts
• K-means workflow
• Interpreting clusters

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.