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"--
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| 主要作者: | |
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| 格式: | Sách giấy |
| 出版: |
Chichester, West Sussex ; Hoboken, NJ. :
Wiley,
2011.
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| 丛编: | Wiley series in computational statistics.
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| 主题: | |
| 在线阅读: | Cover image |
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| Thư viện lưu trữ: | Thư viện Trường Đại học Đà Lạt |
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| 总结: | "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"-- "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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| 实物描述: | xxiv, 689 p. : ill. ; 25 cm. |
| 参考书目: | Includes bibliographical references and index. |
| ISBN: | 9780470688298 (hardback) |