Cluster analysis is used in data mining and is a common technique for statistical data analysis used in many fields of study, such as the medical & life sciences, behavioral & social sciences, engineering, and in computer science. This book is applicable to either a course on clustering and classification or as a companion text for a first class in applied statistics. It features: puts emphasis on illustrating the underlying logic in making decisions during the cluster analysis; brings out the related applications of statistics: Ward's method (ANOVA), JAN (regression analysis & correlational analysis), cluster validation (hypothesis testing, goodness-of-fit, Monte Carlo simulation, etc.); and, includes separate chapters on JAN and the clustering of categorical data.

Review:

"Cluster Analysis and Data Mining: An Introduction pairs a DVD of appendix references on clustering analysis using SPSS, SAS, and more with a discussion designed for training industry professionals and students, and assumes no prior familiarity in clustering or its larger world of data mining. It provides theories, real-world applications, and pairs these with case histories and examples to support algorithms for clustering data and gathering their results. From different clustering models, their applications, and their uses to exercises and reviews designed to reinforce learning, this is a solid reference for any just beginning to delve into the specifics of data mining operations and options."-- (06/01/2015)

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