<p> <br/></p><p>Contents<br/>About This Book............................................................................ ix<br/>Contributing Authors..................................................................... xi<br/>CHAPTER 1 What’s It All About?....................................................... 1<br/>1.1 Data Mining and Machine Learning.................................... 1<br/>1.2 Simple Examples: The Weather Problem<br/>and Others.......................................................................... 7<br/>1.3 Fielded Applications........................................................... 20<br/>1.4 Machine Learning and Statistics......................................... 27<br/>1.5 Generalization as Search..................................................... 28<br/>1.6 Data Mining and Ethics....................................................... 32<br/>1.7 Resources............................................................................ 34<br/>CHAPTER 2 Data Acquisition and Integration................................ 37<br/>2.1 Introduction........................................................................ 37<br/>2.2 Sources of Data................................................................... 37<br/>2.3 Variable Types.................................................................... 39<br/>2.4 Data Rollup......................................................................... 41<br/>2.5 Rollup with Sums, Averages, and Counts.......................... 48<br/>2.6 Calculation of the Mode..................................................... 49<br/>2.7 Data Integration.................................................................. 50<br/>CHAPTER 3 Data Preprocessing........................................................ 57<br/>3.1 Why Preprocess the Data?.................................................. 58<br/>3.2 Descriptive Data Summarization........................................ 61<br/>3.3 Data Cleaning...................................................................... 72<br/>3.4 Data Integration and Transformation................................. 78<br/>3.5 Data Reduction................................................................... 84<br/>3.6 Data Discretization and Concept<br/>Hierarchy Generation......................................................... 98</p><br>xmok77
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