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Data mining and statistics for decision making /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Data mining and statistics for decision making // St�ephane Tuff�ery.
作者:	Tuffery, St�ephane.
出版者:	Chichester, West Sussex ;Wiley, : 2011.,
面頁冊數:	xxiv, 689 p. :ill. ; : 25 cm.;
標題:	Data mining. -
電子資源:	http://onlinelibrary.wiley.com/book/10.1002/9780470979174
ISBN:	9780470688298 (hardback)

Data mining and statistics for decision making /
Tuffery, St�ephane.

Data mining and statistics for decision making /St�ephane Tuff�ery. - Chichester, West Sussex ;Wiley,2011. - xxiv, 689 p. :ill. ;25 cm. - Wiley series in computational statistics. - Wiley series in computational statistics..

Includes bibliographical references and index.

Overview of data mining -- The development of a data mining study -- Data exploration and preparation -- Using commercial data -- Statistical and data mining software -- An outline of data mining methods -- Factor analysis -- Neural networks -- Cluster analysis -- Asociation analysis -- Classification and prediction methods -- An application of data mining: scoring -- Factors for success in a data mining project -- Text mining -- Web mining -- Appendix A: Elements of statistics -- Appendix B: further reading.

"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"--

ISBN: 9780470688298 (hardback)

LCCN: 2010039789

Nat. Bib. Agency Control No.: 015629743UkSubjects--Topical Terms:

225309
Data mining.

LC Class. No.: QA76.9.D343 / T84 2011

Dewey Class. No.: 006.3/12

Data mining and statistics for decision making /
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300 $a xxiv, 689 p. : $b ill. ; $c 25 cm.
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505 0 $a Overview of data mining -- The development of a data mining study -- Data exploration and preparation -- Using commercial data -- Statistical and data mining software -- An outline of data mining methods -- Factor analysis -- Neural networks -- Cluster analysis -- Asociation analysis -- Classification and prediction methods -- An application of data mining: scoring -- Factors for success in a data mining project -- Text mining -- Web mining -- Appendix A: Elements of statistics -- Appendix B: further reading.
520 $a "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"-- $c Provided by publisher.
520 $a "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"-- $c Provided by publisher.
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