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 Strategic Risk Assessment based on Organizational Mode 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