数据挖掘：实用机器学习工具与技术（英文版·第3版）

　　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

　　    Ian H. Witten, Eibe Frank and Mark A. Hall: Data Mining: Practical Machine Learning Tools and Techniques， Third Edition (ISBN 978-0-12-374856-0).
　　    Original English language edition copyright  2011 by Elsevier Inc. All rights reserved.
　　    Authorized English language reprint edition published by the Proprietor.
　　    Copyright  2012 by Elsevier (Singapore) Pte Ltd.
　　    Printed in China by China Machine Press under special arrangement with Elsevier (Singapore) Pte Ltd. This edition is authorized for sale in China only, excluding Hong Kong, Macao SARs and Taiwan.
　　    Unauthorized export of this edition is a violation of the Copyright Act. Violation of this Law is subject to Civil and Criminal Penalties.