(eBook PDF) Applied Predictive Modeling 2nd 2018 Edition

(eBook PDF) Applied Predictive Modeling 2nd 2018 Edition – Digital Ebook – Instant Delivery Download

Product details:

• ISBN-10 ‏ : ‎ 1461468485
• ISBN-13 ‏ : ‎ 978-1461468486
• Author: Max Kuhn , Kjell Johnson

Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning.  The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems.  Addressing practical concerns extends beyond model fitting to topics such as handling class imbalance, selecting predictors, and pinpointing causes of poor model performance―all of which are problems that occur frequently in practice.

Table contents:

1. Introduction
2. A Short Tour of the Predictive Modeling Process
3. Data Pre-processing
4. Over-Fitting and Model Tuning
5. Measuring Performance in Regression Models
6. Linear Regression and Its Cousins
7. Nonlinear Regression Models
8. Regression Trees and Rule-Based Models
9. A Summary of Solubility Models
10. Case Study: Compressive Strength of Concrete Mixtures
11. Measuring Performance in Classification Models
12. Discriminant Analysis and Other Linear Classification Models
13. Nonlinear Classification Models
14. Classification Trees and Rule-Based Models
15. A Summary of Grant Application Models
16. A Summary of Grant Application Models

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