You are not signed in. Sign in.

List Books: Buy books on ListBooks.org

Data Mining Techniques » (2nd Edition)

Book cover image of Data Mining Techniques by Gordon S. Linoff

Authors: Gordon S. Linoff, Michael J. A. Berry
ISBN-13: 9780471470649, ISBN-10: 0471470643
Format: Paperback
Publisher: Wiley, John & Sons, Incorporated
Date Published: March 2004
Edition: 2nd Edition

Find Best Prices for This Book »

Author Biography: Gordon S. Linoff

MICHAEL J. A. BERRY and GORDON S. LINOFF are the founders of Data Miners, Inc., a consultancy specializing in data mining. They have jointly authored some of the leading data mining titles in the field, Data Mining Techniques, Mastering Data Mining, and Mining the Web (all from Wiley). They each have more than a decade of experience applying data mining techniques to business problems in marketing and customer relationship management.

Book Synopsis

The unparalleled author team of Berry and Linoff are back with an invaluable revised edition to their groundbreaking text

The world of data mining has changed tremendously since the publication of the first edition of Data Mining Techniques in 1997. For the most part, the underlying algorithms have remained the same, but the software in which the algorithms are imbedded, the databases to which they are applied, and the business problems they are used to solve have all grown and evolved. With that in mind, Michael Berry and Gordon Linoff–the leading authorities on the use of data mining techniques for business applications–have written a new edition to show you how to harness fundamental data mining methods and techniques to solve common types of business problems.

Berry and Linoff’s years of hands-on data mining experience is reflected in every chapter of this extensively updated and revised edition. They discuss core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis. In addition, they provide an overview of data mining best practices. Each chapter covers a new data mining technique and then immediately explains how to apply the technique for improved marketing, sales, and customer support. The authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data mining for both business professionals and students.

With more than forty percent new and updated material, this second edition of Data Mining Techniques shows you how to:

  • Create stable and accurate predictive models
  • Prepare data for analysis
  • Create the necessary infrastructure for data mining at your company

The companion Web site provides exercises for each chapter, plus data that can be used to test out the various data mining techniques in the book.

Table of Contents

Acknowledgments
About the authors
Introduction
Ch. 1Why and what is data mining?1
Ch. 2The virtuous cycle of data mining21
Ch. 3Data mining methodology and best practices43
Ch. 4Data mining applications in marketing and customer relationship management87
Ch. 5The lure of statistics : data mining using familiar tools123
Ch. 6Decision trees165
Ch. 7Artificial neural networks211
Ch. 8Nearest neighbor approaches : memory-based reasoning and collaborative filtering257
Ch. 9Market basket analysis and association rules287
Ch. 10Link analysis321
Ch. 11Automatic cluster detection349
Ch. 12Knowing when to worry : hazard functions and survival analysis in marketing383
Ch. 13Genetic algorithms421
Ch. 14Data mining throughout the customer life cycle447
Ch. 15Data warehousing, OLAP, and data mining473
Ch. 16Building the data mining environment513
Ch. 17Preparing data for mining539
Ch. 18Putting data mining to work597
Index615

Subjects