Generalized linear models

Generalized linear models (GLMs) refer to a larger framework of prediction techniques which can include linear regression, logistic regression (used to predict binary outcomes), and poisson regression (used to predict counts). They are a generalization of linear regression techniques which allow you to work with other distributions which have non-normal error terms. GLMs can be implemented in R by using the glm package, in which you supply a link function to specify which distribution you are modeling. That makes it easier to work with different types of models within a single package, using standard syntax.

Linear regression using GLM

In Chapter 1, Getting Started with Predictive Analytics, our original...