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 copyright2011 by Elsevier Inc. All rights reserved. Authorized English language reprint edition published by the Proprietor. Copyright2012 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.
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
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