Cluster Analysis and Data Mining (Paperback)

Ronald S. King

ISBN 10: 1938549384 / ISBN 13: 9781938549380

Published by Mercury Learning & Information, 2014

About this Item

Paperback. No detailed description available for "Cluster Analysis and Data Mining". Designed for training industry professionals or for a course on clustering and classification, this book can also be used as a companion text for applied statistics. No previous experience in clustering or data mining is assumed. Informal algorithms for clustering data and interpreting results are emphasized. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781938549380

Bibliographic Details

Title: Cluster Analysis and Data Mining (Paperback)

Publisher: Mercury Learning & Information

Publication Date: 2014

Binding: Paperback

Condition: new

About this title

Synopsis:

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)