This book arose out of a data mining course at MIT’s Sloan School of Management. Preparation for the course revealed that there are a number of excellent books on the business context of data mining, but their coverage of the statistical and machine learn
Foreword
Preface
Acknowledgments
1. Introduction
2. Overview of the Data Mining Process
3. Data Exploration and Dimension Reduction
4. Evaluating Classification and Predictive Performance
5. Multiple Linear Regression
6. Three Simple Classification Metho
Galit Shmueli is Assistant Professor of Statistics in the Department of Decision & Information Technologies of the Robert H. Smith School of Business at the University of Maryland. Her main research areas include models for unique data structures, discret
As a textbook or supplement for courses in data mining, data warehousing, business intelligence, and/or decision support systems at the upper undergraduate or beginning graduate (MS, Ph.D., or MBA) levels in departments of mathematics and statistics, comp
