Publisher description for Data mining methods and models / Daniel T. Larose.


Bibliographic record and links to related information available from the Library of Congress catalog


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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


Library of Congress subject headings for this publication:
Data mining.