Introduction to Data Mining

Author: Tan, Steinbach (USA)
Publisher:
Publish Date: 2006-05-01
Features: This book comprehensively introduces the theory and methods of data mining, aiming to provide readers with the necessary knowledge to apply data mining to practical problems. The book covers five themes: Data, Classification, Association Analysis, Clustering, and Anomaly Detection. Except for Anomaly Detection, each theme includes two chapters: the first chapter discusses basic concepts, representative algorithms, and evaluation techniques, while the second chapter delves deeper into advanced concepts and algorithms. The purpose is to enable readers to thoroughly understand the fundamentals of data mining while also exploring important advanced topics. Additionally, the book provides numerous examples, figures, and exercises. This book is suitable as a textbook for senior undergraduate and graduate students in relevant fields taking data mining courses, as well as a reference for researchers and developers in data mining and application development... The book covers five themes: Data, Classification, Association Analysis, Clustering, and Anomaly Detection, comprehensively introducing the theory and methods of data mining and providing the necessary knowledge to apply data mining to practical problems.