Data Mining Techniques / Edition 2

Data Mining Techniques / Edition 2

by Michael J. Berry, Gordon S. Linoff
     
 

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

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Overview

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.

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Product Details

ISBN-13:
9780471470649
Publisher:
Wiley
Publication date:
03/29/2004
Edition description:
REV
Pages:
672
Product dimensions:
7.40(w) x 9.28(h) x 1.38(d)

Table of Contents

Acknowledgments.

About the Authors.

Introduction.

Chapter 1: Why and What Is Data Mining?

Chapter 2: The Virtuous Cycle of Data Mining.

Chapter 3: Data Mining Methodology and Best Practices.

Chapter 4: Data Mining Applications in Marketing and Customer Relationship Management.

Chapter 5: The Lure of Statistics: Data Mining Using Familiar Tools.

Chapter 6: Decision Trees.

Chapter 7: Artificial Neural Networks.

Chapter 8: Nearest Neighbor Approaches: Memory-Based Reasoning and Collaborative Filtering.

Chapter 9: Market Basket Analysis and Association Rules.

Chapter 10: Link Analysis.

Chapter 11: Automatic Cluster Detection.

Chapter 12: Knowing When to Worry: Hazard Functions and Survival Analysis in Marketing.

Chapter 13: Genetic Algorithms.

Chapter 14: Data Mining throughout the Customer Life Cycle.

Chapter 15: Data Warehousing, OLAP, and Data Mining.

Chapter 16: Building the Data Mining Environment.

Chapter 17: Preparing Data for Mining.

Chapter 18: Putting Data Mining to Work.

Index.

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