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Cluster Analysis and Data Mining Cover

Cluster Analysis and Data Mining

An Introduction

Paid access
|May 2015
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Print: Available at Amazon
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 info@merclearning.com.

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.
PDF ISBN: 978-1-938549-39-7 | E-Pub ISBN: 978-1-942270-13-3 | Paperback ISBN: 978-1-938549-38-0 | DOI: 10.1515/9781938549397
Publisher: Mercury Learning and Information
Copyright owner: © 2014 Walter de Gruyter GmbH, Berlin/Boston
Publication date: 2015
Language: English
Pages: 300