The authors thank the many people who assisted us in improving the first edition and improving it further in the second edition. Anthony Babinec, who has been using drafts of this book for years in his data mining courses at statistics.com, provided us with detailed and expert corrections. Similarly, Dan Toy and John Elder IV greeted our project with enthusiasm and provided detailed and useful comments on earlier drafts. Boaz Shmueli and Raquelle Azran gave detailed editorial comments and suggestions on both editions; Bruce McCullough and Adam Hughes did the same for the first edition. Ravi Bapna, who used an early draft in a data mining course at the Indian School of Business, provided invaluable comments and helpful suggestions. Useful comments and feedback have also come from the many instructors, too numerous to mention, who have used the book in their classes.
From the Smith School of Business at the University of Maryland, colleagues Shrivardhan Lele, Wolfgang Jank, and Paul Zantek provided practical advice and comments. We thank Robert Windle, and MBA students Timothy Roach, Pablo Macouzet, and Nathan Birckhead for invaluable datasets. We also thank MBA students Rob Whitener and Daniel Curtis for the heatmap and map charts. And we thank the many MBA students for fruitful discussions and interesting data mining projects that have helped shape and improve the book.
This book would not have seen the light of day without the nurturing support of the faculty at the Sloan School of Management at MIT. Our special thanks to Dimitris Bertsimas, James Orlin, Robert Freund, Roy Welsch, Gordon Kaufmann, and Gabriel Bitran. As teaching assistants for the data mining course at Sloan, Adam Mersereau gave detailed comments on the notes and cases that were the genesis of this book, Romy Shioda helped with the preparation of several cases and exercises used here, and Mahesh Kumar helped with the material on clustering. We are grateful to the MBA students at Sloan for stimulating discussions in the class that led to refinement of the notes as well as XLMiner.
Chris Albright, Gregory Piatetsky-Shapiro, Wayne Winston, and Uday Karmarkar gave us helpful advice on the use of XLMiner. Anand Bodapati provided both data and advice. Suresh Ankolekar and Mayank Shah helped develop several cases and provided valuable pedagogical comments. Vinni Bhandari helped write the Charles Book Club case.
We would like to thank Marvin Zelen, L. J. Wei, and Cyrus Mehta at Harvard, as well as Anil Gore at Pune University, for thought-provoking discussions on the relationship between statistics and data mining. Our thanks to Richard Larson of the Engineering Systems Division, MIT, for sparking many stimulating ideas on the role of data mining in modeling complex systems. They helped us develop a balanced philosophical perspective on the emerging field of data mining.
Our thanks to Ajay Sathe, who energetically shepherded XLMiner's development over the years and continues to do so, and to his colleagues on the XLMiner team: Suresh Ankolekar, Poonam Baviskar, Kuber Deokar, Rupali Desai, Yogesh Gajjar, Ajit Ghanekar, Ayan Khare, Bharat Lande, Dipankar Mukhopadhyay, S. V. Sabnis, Usha Sathe, Anurag Srivastava, V. Subramaniam, Ramesh Raman, and Sanhita Yeolkar.
Steve Quigley at Wiley showed confidence in this book from the beginning and helped us navigate through the publishing process with great speed. Curt Hinrichs' vision, tips, and encouragement helped bring this book to the starting gate. We are also grateful to Ashwini Kumthekar, Achala Sabane, Michael Shapard, and Heidi Sestrich who assisted with typesetting, figures, and indexing, and to Valerie Troiano who has shepherded many instructors through the use of XLMiner and early drafts of this text.
We also thank Catherine Plaisant at the University of Maryland's Human-Computer Interaction Lab, who helped out in a major way by contributing exercises and illustrations to the data visualization chapter, Marietta Tretter at Texas A&M for her helpful comments and thoughts on the time series chapters, and Stephen Few and Ben Shneiderman for feedback and suggestions on the data visualization chapter and overall design tips.