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Preface .1 Introduction2 Overview of Supervised Learning2.1 Introduction2.2 Variable Types and Terminology2.3 Two Simple Approaches to Prediction: Least Squares and Nearest Neighbors2.4 Statistical Decision Theory2.5 Lo.cal Methods in High Dimensions2.6 Statistical Models, Supervised Learning and Function Approximation2.7 Structured Regression Models2.8 Classes of Restricted Estimators2.9 Model Selection and the Bias-Variance TradeoffBibliographic NotesExercises3 Linear Methods for Regression3.1
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