We consider generalized linear regression with many highly correlated regressors-for instance, digitized points of a curve on a spatial or temporal domain. We refer to this setting as signal ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous or discrete ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Compared to standard linear ...