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 learning algorithms and theoretical underpinnings is not sufficiently detailed to provide a practical guide for users who possess the raw skills and tools to analyze data. This book is intended for the business student (and practitioner) of data mining techniques, and the goal is threefold: (1) to provide both a theoretical and practical understanding of the key methods of classification, prediction, reduction and exploration that are at the heart of data mining; (2) to provide a business decision-making context for these methods; and (3) using real business cases and data, to illustrate the application and interpretation of these methods. The book employs the use of an Excel add-in, XLMinerTM, at no cost to registered instructors, in order to illustrate and interpret the various data sets that are presented throughout. Real-life business cases are also presented so that readers can implement algorithms with a very low learning hurdle.
- The chapters have been written with flexibility in mind so the user and/or instructor can navigate throughout the book as he or she chooses.
- The excellent mix between mathematical rigor and readability make the book ideal for multiple readerships.
- The software system-of-choice, XLMinerTM, is a familiar and easy-to-use tool for business analysts, consultants, and students since it is based on the popular Excel spreadsheet concept. It provides a comprehensive set of data mining models and algorithms that includes statistical, machine learning and database methods - at no additional cost to the purchaser!
- There are plentiful exercises and examples to motivate learning and understanding.
- Paperback: 298 pages
- Publisher: Wiley (12 September 2008)
- Language: English
- ISBN-10: 8126517581
- ISBN-13: 978-8126517589
- Product Dimensions: 21.4 x 14.9 x 1.9 cm