The only thorough, comprehensive book available on clustering
From two of the best-known experts in the field comes the first book to take a truly comprehensive look at clustering. The book begins with a complete introduction to cluster analysis in which readers will become familiarized with classification and clustering; definition of clusters; clustering applications; and the literature of clustering algorithms. The authors then present a detailed outline of the book's content and go on to explore:
Proximity measures
Hierarchical clustering
Partition clustering
Neural network-based clustering
Kernel-based clustering
Sequential data clustering
Large-scale data clustering
Data visualization and high-dimensional data clustering
Cluster validation
The authors assume no previous background in clustering and their generous inclusion of examples and references help make the subject matter comprehensible for readers of varying levels and backgrounds. The book is intended as a professional reference for computer scientists and applied mathematicians working with data-intensive applications, and for computational intelligence researchers who use clustering for feature selection or data reduction. Its selection of homework exercises also makes it appropriate as a textbook for graduate students in mathematics, science, and engineering.
