Applied Predictive Modeling

Max Kuhn and Kjell Johnson
Additional contact information
Max Kuhn: Pfizer Global Research and Development, Division of Nonclinical Statistics
Kjell Johnson: Arbor Analytics

in Springer Books from Springer

Date: 2013
ISBN: 978-1-4614-6849-3
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Chapters in this book:

Ch Chapter 1 Introduction

Max Kuhn and Kjell Johnson

Ch Chapter 10 Case Study: Compressive Strength of Concrete Mixtures

Max Kuhn and Kjell Johnson

Ch Chapter 11 Measuring Performance in Classification Models

Max Kuhn and Kjell Johnson

Ch Chapter 12 Discriminant Analysis and Other Linear Classification Models

Max Kuhn and Kjell Johnson

Ch Chapter 13 Nonlinear Classification Models

Max Kuhn and Kjell Johnson

Ch Chapter 14 Classification Trees and Rule-Based Models

Max Kuhn and Kjell Johnson

Ch Chapter 15 A Summary of Grant Application Models

Max Kuhn and Kjell Johnson

Ch Chapter 16 Remedies for Severe Class Imbalance

Max Kuhn and Kjell Johnson

Ch Chapter 17 Case Study: Job Scheduling

Max Kuhn and Kjell Johnson

Ch Chapter 18 Measuring Predictor Importance

Max Kuhn and Kjell Johnson

Ch Chapter 19 An Introduction to Feature Selection

Max Kuhn and Kjell Johnson

Ch Chapter 2 A Short Tour of the Predictive Modeling Process

Max Kuhn and Kjell Johnson

Ch Chapter 20 Factors That Can Affect Model Performance

Max Kuhn and Kjell Johnson

Ch Chapter 3 Data Pre-processing

Max Kuhn and Kjell Johnson

Ch Chapter 4 Over-Fitting and Model Tuning

Max Kuhn and Kjell Johnson

Ch Chapter 5 Measuring Performance in Regression Models

Max Kuhn and Kjell Johnson

Ch Chapter 6 Linear Regression and Its Cousins

Max Kuhn and Kjell Johnson

Ch Chapter 7 Nonlinear Regression Models

Max Kuhn and Kjell Johnson

Ch Chapter 8 Regression Trees and Rule-Based Models

Max Kuhn and Kjell Johnson

Ch Chapter 9 A Summary of Solubility Models

Max Kuhn and Kjell Johnson

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DOI: 10.1007/978-1-4614-6849-3

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