Model-combining (i.e., mixing) methods have been proposed in recent years to deal with uncertainty in model selection. Even though advantages of model combining over model selection have been ...

This paper discusses the problem of choosing a linear model from a set of nested alternatives. Two popular devices for selecting a model in this situation have been model selection criteria and ...

Businesspeople need to demand more from machine learning so they can connect data scientists’ work to relevant action. This requires basic machine learning literacy — what kinds of problems can ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Linear regression models the relationship between a dependent and independent variable(s). A linear regression essentially estimates a line of best fit among all variables in the model. Regression ...