Finding Groups in Data: An Introduction to Cluster Analysis Leonard Kaufman, Peter J. Rousseeuw
Publisher: Wiley-Interscience

Finding Groups in Data: An Introduction to Cluster Analysis. € John Wiley & Sons, 1990 Collective Intelligence. You can also use cluster analysis to summarize data rather than to find "natural" or "real" clusters; this use of clustering is sometimes called dissection. Clustering Large and High Dimensional data. Cluster analysis is one of those techniques I don't get to use very often. About once every couple of years someone will be doing a study of types of companies, patients or clients and have a need for a cluster analysis. If the data were analyzed through cluster analysis, cat and dog are more likely to occur in the same group than cat and horse. Researchers have noted that people find it a natural task. Audience The following groups will find this book a valuable tool and reference: applied statisticians; engineers and scientists using data analysis; researchers in pattern recognition, artificial intelligence, machine learning, and data mining; and applied mathematicians. Kogan J., Nicholas C., Teboulle M. Instructors can also use it as a textbook for an introductory course in cluster analysis or as source material for a graduate-level introduction to data mining. You can This is a general introduction to free-listing. The purpose of cluster analysis is to place objects into groups, or clusters, suggested by the data, not defined by a priori, such that objects in a given cluster tend to be similar to each other in some sense, and objects in different clusters tend to be dissimilar.