Introduction to Data Mining

Author: (USA) Tan Michael Steinbach, Vipin
Publisher:
Publish Date: 2006-01-01
Features: This book provides a comprehensive introduction to data mining, aiming to equip readers with the knowledge necessary to apply data mining to real-world problems. The book covers five main topics: data, classification, association analysis, clustering, and anomaly detection. Except for anomaly detection, each topic has two chapters: the first chapter introduces basic concepts, representative algorithms, and evaluation techniques, while the second chapter delves deeper into advanced concepts and algorithms. The goal is to help readers thoroughly understand the fundamentals of data mining while also exploring important advanced topics. Additionally, the book includes 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 technical professionals engaged in data mining research and application development.