Vol 65

A practical, user-oriented introduction to clustering methods, including both hierarchical and non-hierarchical methods. Shows how clustering can be used to interpret large quantities of analytical data and discusses the relation of clustering to other pattern recognition techniques. Uses a two-level approach to provide both a qualitative understanding of the philosophy, advantages, and disadvantages of clustering and a quantitative understanding for readers who want a strong mathematical background. Includes a worked example and a list of computer packages.