... The text is easy to read as each chapter focuses on a particular algorithm and a consistent presentation style has been adopted throughout the book ... Each chapter was reviewed by two independent reviewers and one of the book editors-resulting in a text that will be a useful reference source for years to come. -International Statistical Review, 2010 If you are a quality professional looking for data analysis techniques beyond multiple regression, and you are comfortable reading high level mathematics, then this book may be for you. -Journal of Quality Technology, Vol. 41, No. 4, October 2009
From classification and clustering to statistical learning, association analysis, and link mining, this book covers the most important topics in data mining research. It presents the ten most influential algorithms used in the data mining community today. Each chapter provides a detailed description of the algorithm, a discussion of available software implementation, advanced topics, and exercises. With a simple data set, examples illustrate how each algorithm works and highlight the overall performance of each algorithm in a real-world application. Featuring contributions from leading researchers, this reference is useful for both professionals and students.