A Primer on Cluster Analysis: 4 Basic Methods That (Usually) Work [Book Review]

This book examine the concept of clustering. Clustering was important in the past, has become more important in the present era of internet, social networks, and big data, and will continue to remain so in future. We need clustering to find subgroups of cancers, clusters of stars in our galaxies, to answer web queries, to understand group dynamics in social networks—the list goes on. The book develops the necessary concepts such as similarity, distance, clusters, computer view point, human view point, and cluster validation in a very logical and lucid manner with plenty of easy-to-follow examples and creative pictures. Although the book primarily focuses on four types of popular clustering algorithms, it provides adequate materials and pointers for interested readers to sail through a much wider family of clustering algorithms. This book will be very useful (and of course enjoyable to read) to a wide spectrum of readers including beginners, researchers, and practitioners. It consists of 11 chapters divided into two parts: Part I: The Art and Science of Clustering, which has five chapters and Part II: Four Basic Models & Algorithms that contains the remaining six chapters.