ABSTRACT

This text provides a modern introduction to regression and classification with an emphasis on big data and R. Each chapter is partitioned into a main body section and an extras section. The main body uses math stat very sparingly and always in the context of something concrete, which means that readers can skip the math stat content entirely if they wish. The extras section is for those who feel comfortable with analysis using math stat.

chapter 1|63 pages

Setting the Stage

chapter 2|58 pages

Linear Regression Models

chapter 4|31 pages

Generalized Linear and Nonlinear Models

chapter 5|35 pages

Multiclass Classification Problems

chapter 6|51 pages

Model Fit Assessment and Improvement

chapter 7|44 pages

Disaggregating Regressor Effects

chapter 8|27 pages

Shrinkage Estimators

chapter 9|52 pages

Variable Selection and Dimension Reduction

chapter 10|14 pages

Partition-Based Methods

chapter 11|26 pages

Semi-Linear Methods

chapter 12|20 pages

Regression and Classification in Big Data