Table of Contents
1. Introduction
How Clustering Methods Are Used
Data Sets to Be Used as Examples
A Few Cautions about Cluster Analysis
2. Similarity Measures
Terminology
The Concept of Similarity
The Choice of Variables
Similarity Measures
Suggested Reading
3. A Review of Clustering Methods
On the Nature of Clusters
Hierarchical Agglomerative Methods
Iterative Partitioning Methods
Factor Analysis Variants
Other Methods
Determining the Number of Clusters
Comparing Clustering Methods
Suggested Reading
4. Validation Techniques
Cophenetic Correlation
Significance Tests on Variables Used to Create Clusters
Replication
Significance Tests on External Variables
Monte Carlo Procedures
5. Cluster Analysis Software and the Literature on Clustering
Collections of Subroutines and Algorithms
Statistical Packages Containing Clustering Software
Cluster Analysis Packages
Simple Cluster Analysis Programs
The Literature on Cluster Analysis
Guide to Reporting Cluster Analysis Studies
Appendix: Example Data Sets (Burial Data)