1 Introduction
1.1 Prediction Versus Interpretation
1.2 Key Ingredients of Predictive Models
1.3 Terminology
1.4 Example Data Sets and Typical Data Scenarios
1.5 Overview
1.6 Notation
Part Ⅰ General Strategies
2 A Short Tour of the Predictive Modeling Process
2.1 Case Study:Predicting Fuel Economy
2.2 Themes
2.3 Summary
3 Data Pre-processing
3.1 Case Study:Cell Segmentation in High-Content Screening
3.2 Data Transformations for Individual Predictors
3.3 Data Transformations for Multiple Predictors
3.4 Dealing with Missing Values
3.5 Removing Predictors
3.6 Adding Predictors
3.7 Binning Predictors
3.8 Computing
Exercises
4 Over-Fitting and Model Tuning
4.1 The Problem of Over-Fitting
4.2 Model Tuning
4.3 Data Splitting
4.4 Resampling Techniques
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