Cluster Analysis and Data Mining - An Introduction (Paperback)

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. Designed for training industry professionals or for a course on clustering and classification, it 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. In order to evaluate the results of clustering and to explore data, graphical methods and data structures are used for representing data. Throughout the text, examples and references are provided, in order to enable the material to be comprehensible for a diverse audience. A companion disc includes numerous appendices with programs, data, charts, solutions, etc. eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at [email protected]. Features: Places emphasis on illustrating the underlying logic in making decisions during the cluster analysis Discusses the related applications of statistic, e.g., Ward's method (ANOVA), JAN (regression analysis & correlational analysis), cluster validation (hypothesis testing, goodness-of-fit, Monte Carlo simulation, etc.) Contains separate chapters on JAN and the clustering of categorical data Includes a companion disc with solutions to exercises, programs, data sets, charts, etc.

General

Imprint:	Mercury Learning & Information
Country of origin:	United States
Release date:	October 2014
First published:	July 2014
Authors:	Ronald S. King
Dimensions:	229 x 178 x 16mm (L x W x T)
Format:	Paperback
Pages:	300
ISBN-13:	978-1-938549-38-0
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > Applications of computing > Databases > Data mining Promotions
LSN:	1-938549-38-4
Barcode:	9781938549380

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