Data Mining: Practical Machine Learning Techniques (2nd Edition)

Author: Ian H. Witten (New Zealand) Frank
Publisher:
Publishing Time: Not available
Features: This book is logically rigorous, comprehensive in content, and highly practical, making it suitable as a textbook for undergraduate or graduate students in higher education institutions. It can also be referenced by relevant technical personnel. The book introduces the basic theory and practical methods of data mining. The main content includes various models (decision trees, association rules, linear models, clustering, Bayesian networks, and neural networks) and their applications in practice, as well as an analysis of their limitations. It also provides methods for safely cleaning datasets, building, and evaluating the predictive quality of models, and introduces the publicly available data mining platform Weka. The Weka system features a graphical user interface for performing data mining tasks, which helps in understanding the models. It is a practical and widely popular tool.