Data mining and statistics for decision making

"Data Mining is a practical guide to understanding and implementing data mining techniques, featuring traditional methods such as cluster analysis, factor analysis, linear regression, PLS regression and generalised linear models"-- Provided by publisher

Bibliographic Details
Main Author: Tuffery, Stephane (Author)
Format: Book
Language:English
Published: Chichester, West Sussex ; Hoboken, New Jersey : Wiley , c2011
Series:Wiley series in computational statistics
Subjects:
Online Access:Cover image
Description
Summary:"Data Mining is a practical guide to understanding and implementing data mining techniques, featuring traditional methods such as cluster analysis, factor analysis, linear regression, PLS regression and generalised linear models"-- Provided by publisher
"This practical guide to understanding and implementing data mining techniques discusses traditional methods--cluster analysis, factor analysis, linear regression, PLS regression, and generalized linear models--and recent methods--bagging and boosting, decision trees, neural networks, support vector machines, and genetic algorithm. The book focuses largely on credit scoring, one of the most common applications of predictive techniques, but also includes other descriptive techniques, such as customer segmentation. It also covers data mining with R, provides a comparison of SAS and SPSS, and includes an appendix presenting the necessary statistical background"-- Provided by publisher
Physical Description:xxiv, 689 p. : ill. ; 25 cm.
Bibliography:Includes bibliographical references and index
ISBN:0470688297 (hardback : alk. paper)
9780470688298 (hardback : alk. paper)