Data mining and statistics for decision making /
"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 v...
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| Format: | eBook |
| Language: | English |
| Published: |
Chichester, West Sussex ; Hoboken, NJ :
Wiley,
2011.
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| Series: | Wiley Online Library.
Wiley series in computational statistics. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | "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"-- |
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| Item Description: | Electronic resource. |
| Physical Description: | 1 online resource (xxiv, 689 pages) : illustrations |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9780470979174 (electronic bk.) 0470979178 (electronic bk.) |