Author(s) Name:  Gordon S. Linoff, Michael J. A. Berry
This new edition—more than 50% new and revised— is a significant update from the previous one, and shows you how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company.
Data Mining Techniques, Third Edition covers a new data mining technique with each successive chapter and then demonstrates how you can apply that technique for improved marketing, sales, and customer support to get immediate results.
Table of contents
Chapter 1 What Is Data Mining and Why Do It?
Chapter 2 Data Mining Applications in Marketing and Customer Relationship Management
Chapter 3 The Data Mining Process
Chapter 4 Statistics 101: What You Should Know About Data
Chapter 5 Descriptions and Prediction: Profiling and Predictive Modeling
Chapter 6 Data Mining Using Classic Statistical Techniques
Chapter 7 Decision Trees
Chapter 8 Artificial Neural Networks
Chapter 9 Nearest Neighbor Approaches: Memory-Based Reasoning and Collaborative Filtering
Chapter 10 Knowing When to Worry: Using Survival Analysis to Understand Customers
Chapter 11 Genetic Algorithms and Swarm Intelligence
Chapter 12 Tell Me Something New: Pattern Discovery and Data Mining
Chapter 13 Finding Islands of Similarity: Automatic Cluster Detection
Chapter 14 Alternative Approaches to Cluster Detection
Chapter 15 Market Basket Analysis and Association Rules
Publisher:  John Wiley & Sons
Year of Publication:  2011
Book Link:  Home Page Url