Data mining methods and models

Provides an introduction into data mining methods and models, including association rules, clustering, K-nearest neighbor, statistical inference, neural networks, linear and logistic regression, and multivariate analysis Presents a unified approach based on CRISP methodology, which involves Strategi...

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Главный автор: Larose, Daniel T.
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Язык:Undetermined
Опубликовано: Hoboken, NJ Wiley-Interscience 2006
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Thư viện lưu trữ: Trung tâm Học liệu Trường Đại học Cần Thơ
Описание
Итог:Provides an introduction into data mining methods and models, including association rules, clustering, K-nearest neighbor, statistical inference, neural networks, linear and logistic regression, and multivariate analysis Presents a unified approach based on CRISP methodology, which involves Strategic Risk Assessment based on Organizational Modelling. A companion Web site features downloads of large data sets used in the chapter projects, with a discussion area and message board, where readers are encouraged to exchange ideas