ABSTRACT

The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

chapter 1|20 pages

Introduction

chapter 4|28 pages

Exploratory Visualizations

chapter 5|28 pages

| Encoding Categorical Predictors

chapter 6|35 pages

Engineering Numeric Predictors

chapter 7|30 pages

Detecting Interaction Effects

chapter 8|18 pages

Handling Missing Data

chapter 9|21 pages

Working with Profile Data

chapter 10|14 pages

Feature Selection Overview

chapter 11|15 pages

Greedy Search Methods

chapter 12|26 pages

Global Search Methods