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...
| Κύριος συγγραφέας: | |
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| Μορφή: | Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Chichester, West Sussex ; Hoboken, NJ. :
Wiley,
2011.
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| Σειρά: | Wiley series in computational statistics.
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| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
| Περίληψη: | "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"-- "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"-- |
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| Φυσική περιγραφή: | 1 online resource (xxiv, 689 pages) : illustrations. |
| Βιβλιογραφία: | Includes bibliographical references and index. |
| ISBN: | 9780470979174 0470979178 9780470979167 047097916X 1283373971 9781283373975 |
| DOI: | 10.1002/9780470979174 |
