《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