2007 / xxii + 466 pages / Softcover / ISBN 978-0-898716-23-8 / List Price $117.50 / ASA-SIAM Member Price $82.25 / Order Code SA20
Cluster analysis is an unsupervised process that divides a set of objects into homogeneous groups. This book starts with basic information on cluster analysis, including the classification of data and the corresponding similarity measures, followed by the presentation of over 50 clustering algorithms in groups according to some specific baseline methodologies such as hierarchical, center-based, and search-based methods. As a result, readers and users can easily identify an appropriate algorithm for their applications and compare novel ideas with existing results.
The book also provides examples of clustering applications to illustrate the advantages and shortcomings of different clustering architectures and algorithms. Application areas include pattern recognition, artificial intelligence, information technology, image processing, biology, psychology, and marketing. Readers also learn how to perform cluster analysis with the C/C++ and MATLAB™ programming languages.
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. 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.
About the Authors
Guojun Gan is a Ph.D. candidate in the Department of Mathematics and Statistics at York University, Ontario, Canada. His research interests include data mining and data clustering, and he is the coauthor of algorithms for clustering categorical data and for subspace/projective clustering of high-dimensional data.
Chaoqun Ma is Professor and the Deputy Dean of the College of Business Administration at Hunan University, People's Republic of China. His main research areas are data mining, financial engineering, and risk management.
Jianhong Wu is a Senior Canada Research Chair in Applied Mathematics at York University, Ontario, Canada. He is the author or coauthor of over 200 peer-reviewed publications and six monographs in the areas of nonlinear dynamical systems, delay differential equations, mathematical biology and epidemiology, neural networks, and pattern formation and recognition.
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