PREFACEUpdated and Revised ContentSecond EditionThird EditionACKNOWLEDGMENTSABOUT THE AUTHORSPART Ⅰ INTRODUCTION TO DATA MININGCHAPTER 1 What's It All About？CHAPTER 2 Input:Concepts,Instances,and AttributesCHAPTER 3 Output:Knowledge RepresentationCHAPTER 4 Algorithms:The Basic MethodsCHAPTER 5 Credibility:Evaluating What's Been LearnedPART Ⅱ ADVANCED DATA MININGCHAPTER 6 Implementations:Real Machine Learning SchemesCHAPTER 7 Data TransformationsCHAPTER 8 Ensemble LearningCHAPTER 9 Moving on:Applications and BeyondPART Ⅲ THE WEKA DATA MINING WORKBENCHCHAPTER 10 Introduction to WekaCHAPTER 11 The ExplorerCHAPTER 12 The Knowledge Flow InterfaceCHAPTER 13 The ExperimenterCHAPTER 14 The Command-Line InterfaceCHAPTER 15 Embedded Machine LearningCHAPTER 16 Writing New Learning SchemesCHAPTER 17 Tutorial Exercises for the Weka ExplorerREFERENCESINDEX