Cluster Analysis and Data Mining: An Introduction

King

ISBN 10: 1938549384 / ISBN 13: 9781938549380

Editore: Mercury Learning and Information, 2014

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2014. Har/Cdr. Paperback. . . . . . Books ship from the US and Ireland.

Codice articolo V9781938549380

Dati bibliografici

• Titolo: Cluster Analysis and Data Mining: An Introduction
• Editore: Mercury Learning and Information
• Data di pubblicazione: 2014
• Lingua: Inglese
• ISBN 10: 1938549384
• ISBN 13: 9781938549380
• Rilegatura: Brossura
• Condizione: New

Descrizione articolo

Riassunto

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.

Informazioni sull?autore

King Ronald S. :

Ronald S. King holds a PhD in applied statistics and currently teaches online courses for Tarleton State University (TX). Spanning a career of four decades of teaching and administration at multiple universities, he brings a unique perspective to the fields of statistics, computer science, and information systems. His lifetime career publications have made numerous contributions to these fields.