Overview
Learn about hierarchical clustering in this comprehensive data mining lecture that covers fundamental clustering concepts and algorithms. Begin with an introduction to clustering fundamentals before exploring various categories of clustering algorithms. Dive deep into hierarchical clustering methods, understanding how to measure cluster proximity and determine optimal stopping points. Examine efficiency considerations in clustering implementations and discover techniques for validating cluster quality. The lecture concludes with practical insights into cluster validation methods, providing a thorough foundation in hierarchical clustering approaches for data mining applications.
Syllabus
Recording starts
Lecture starts
Announcements
Clustering intro
Categories of clustering algos
Hierarchical clustering
"Closeness" of clusters
Choosing when to stop
1: Efficiency
Cluster validation
Lecture ends
Taught by
UofU Data Science