Data mining and statistics for decision making / Stéphane Tufféry. Data mining and statistics for decision making Tuffery, Stéphane. Data mining. Statistical decision. QA76.9.D343 T84 2011 006.312 22 TUD Includes bibliographical references and index. "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. "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. Chichester, West Sussex ; Hoboken, NJ. : Wiley, 2011. 2011. 2011 Text xv, 689 p.: eng Wiley series in computational statistics License restrictions may limit access.