Data mining methods and models

Preface What is data mining? " Data mining is the analysis of (often large) observational data sets to find unsuspected relationships and to summarize the data in novel ways that are both understandable and useful to the data owner. "-Data mining is predicted to be " one of the most revolutionary developments of the next decade " , according to the online technology magazine ZDNET News (February 8, 2001). In fact, the MIT Technology Review chose data mining as one of ten emerging technologies that will change the world. Because data mining represents such an important field, Wiley Interscience and Dr. Daniel T. Larose have teamed up to publish a new series on data mining, initially consisting of three volumes. The first volume in this series, Discovering Knowledge in Data: An Introduction to Data Mining, appeared in 2005, and introduced the reader to this rapidly growing field of data mining. The second volume in the series, Data Mining Methods and Models, explores the process of data mining from the point of view of model building – the development of complex and powerful predictive models that can deliver actionable results for a wide range of business and research problems. Why is this book needed? Data Mining Methods and Models continues the thrust of Discovering Knowledge in Data, providing the reader with: • The models and techniques to uncover hidden nuggets of information, • The insight into how the data mining algorithms really work, and • The experience of actually performing data mining on large data sets. The best way to avoid costly errors stemming from a blind black-box approach to data mining, is to instead apply a " white-box " methodology, which emphasizes an understanding of the algorithmic and statistical model structures underlying the software.