Often considered more of an art than a science, books on clustering have been dominated by learning through example with techniques chosen almost through trial and error. Even the two most popular, and most related, clustering methods-K-Means for partitioning and Ward's method for hierarchical clustering-have lacked the theoretical underpinning req

chapter 1|38 pages

What Is Clustering?

chapter 2|48 pages

What Is Data?

chapter 3|46 pages

K-Means Clustering and Related Approaches

chapter 4|28 pages

Least-Squares Hierarchical Clustering

chapter 6|60 pages

Validation and Interpretation