Publications

Pang-Ning Tan, Michigan State University
Michael Steinbach, University of Minnesota
Vipin Kumar, University of Minnesota and Army High Performance Computing Research Center

Publisher: Pearson Addison Wesley (May, 2005)
Hardcover: 769 pages
ISBN: 0321321367

http://www-users.cs.umn.edu/~kumar/dmbook/

Introduction to Data Mining provides a readable, yet thorough introduction
to data mining for students, instructors, researchers, and professionals.
The book is organized around three core areas: classification, association
analysis, and clustering, and each of these areas is covered in a pair of
chapters: one introductory and one more advanced. The introductory
chapter covers basic concepts, representative algorithms, and evaluation
techniques, while the more advanced chapter discusses advanced concepts
and algorithms. There are also two chapters that discuss data issues,
including pre-processing and visualization, as well as a chapter on
anomaly detection. The objective of the book is to provide the reader with
a sound understanding of the foundations data mining, while still covering
many important advanced topics. Because of this approach, Introduction to
Data Mining is useful as both a learning tool and a reference.

For more information, visit
http://www-users.cs.umn.edu/~kumar/dmbook/ which contains
lecture slides, and links to other data mining resources, such as data
mining algorithms and data sets.