Introduction to cluster analysis -- Overview of data mining -- Hierarchical clustering -- Partition clustering -- Judgmental analysis -- Fuzzy clustering models and applications -- Classification and association rules -- Cluster validity -- Clustering categorical data -- Mining outliers -- Model-based clustering -- General issues.
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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 computer sciences. This book is applicable to either a course on clustering and classification or as a companion text for a first class in applied statistics. This book 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. --