Data Mining ─ A Tutorial-based Primer

This textbook provides a tutorial-based introduction to data mining with a focus on model building and testing, as well as on interpreting and validating results. The book follows the format of the first edition, but with updates and additions throughout. A new chapter on preprocessing and data visualization has been added, along with a new, running case study. The new edition uses the Weka toolkit. Since Weka contains several algorithms for data preprocessing, data visualization, classification, clustering, and association rule mining, the focus of the second edition is on students gaining a firm understanding of a select group of fundamental data mining algorithms.

Richard J. Roiger is a professor emeritus at Minnesota State University, Mankato where he taught and performed research in the Computer & Information Science Department for 27 years. Dr. Roiger’s Ph.D. degree is in Computer & Information Sciences from the University of Minnesota. Dr. Roiger continues to serve as a part-time faculty member teaching courses in data mining, artificial intelligence and research methods. Richard enjoys interacting with his grandchildren, traveling, writing and pursuing his musical talents.