《数据挖掘(实用机器学习工具与技术英文版第3版)》由威滕、弗兰克、霍尔所著，是机器学习和数据挖掘领域的经典畅销教材，被众多国外名校选为教材。书中不仅详细介绍机器学习的基本理论，还对实际工作中应用的相关工具和技术提了一些建议。本版对上一版内容进行了全面更新，以反映自第2版出版以来数据挖掘领域的技术变革和新方法，包括数据转换、集成学习、大规模数据集、多示例学习方面的新材料，以及新版的Weka机器学习软件。
本书逻辑严密、内容翔实、极富实践性，适合作为高等学校本科生或研究生的教材，也可供相关技术人员参考。
PREFACE
Updated and Revised Content
Second Edition
Third Edition
ACKNOWLEDGMENTS
ABOUT THE AUTHORS
PART Ⅰ INTRODUCTION TO DATA MINING
CHAPTER 1 What's It All About？
CHAPTER 2 Input:Concepts,Instances,and Attributes
CHAPTER 3 Output:Knowledge Representation
CHAPTER 4 Algorithms:The Basic Methods
CHAPTER 5 Credibility:Evaluating What's Been Learned
PART Ⅱ ADVANCED DATA MINING
CHAPTER 6 Implementations:Real Machine Learning Schemes
CHAPTER 7 Data Transformations
CHAPTER 8 Ensemble Learning
CHAPTER 9 Moving on:Applications and Beyond
PART Ⅲ THE WEKA DATA MINING WORKBENCH
CHAPTER 10 Introduction to Weka
CHAPTER 11 The Explorer
CHAPTER 12 The Knowledge Flow Interface
CHAPTER 13 The Experimenter
CHAPTER 14 The Command-Line Interface
CHAPTER 15 Embedded Machine Learning
CHAPTER 16 Writing New Learning Schemes
CHAPTER 17 Tutorial Exercises for the Weka Explorer
REFERENCES
INDEX
