Applied predictive modeling / Max Kuhn and Kjell Johnson.

Includes bibliographical references (pages 569-587) and index.

General Strategies. A Short Tour of the Predictive Modeling Process -- Data Pre-processing -- Over-Fitting and Model Tuning -- Regression Models. Measuring Performance in Regression Models -- Linear Regression and Its Cousins -- Nonlinear Regression Models -- Regression Trees and Rule-Based Models -- A Summary of Solubility Models -- Case Study: Compressive Strength of Concrete Mixtures -- Classification Models. Measuring Performance in Classification Models -- Discriminant Analysis and Other Linear Classification Models -- Nonlinear Classification Models -- Classification Trees and Rule-Based Models -- A Summary of Grant Application Models -- Remedies for Severe Class Imbalance -- Case Study: Job Scheduling -- Other Considerations. Measuring Predictor Importance -- An Introduction to Feature Selection -- Factors That Can Affect Model Performance.