11 Clustering

Preparation

Ch 9

Material

Session material: In this folder

Session Description

This lecture covers clustering algorithms.

Key Concepts

• k means
• Hierarchical clustering
• DBSCAN

Learning Objectives

• Describe the following clustering algorithms along with their advantages and disadvantages:
• k-Means
• Agglomerative clustering
• DBSCAN
• Apply the above clustering algorithms in Python
• Evaluate clustering algorithms (e.g. by inspecting the output in 2D-plots or in other ways inspecting which elements are clustered together).
• Use a dendrogram to determine the optimal number of clusters