Balgobin Nandram, Erik Barry Erhardt, Fitting Bayesian Two-Stage Generalized Linear Models Using Random Samples via the SIR Algorithm, Sankhyā: The Indian Journal of Statistics (2003-2007), Vol. 66, ...

Linear regression draws corresponding trend lines, such as disease outbreaks, bitcoin prices, demand for software experts, etc.

What is linear regression? Linear regression is a basic machine learning algorithm that is used for predicting a variable based on its linear relationship between other independent variables.

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 techniques include ordinary linear regression, L1 (lasso) and L2 (ridge) regression, and linear support vector regression (linear SVR). This article presents a demo of linear SVR, implemented ...

An algorithm is presented for nonlinear least squares estimation in which the parameters to be estimated can be regarded as all nonlinear (the traditional approach) or reclassified as linear-nonlinear ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the AdaBoost.R2 algorithm for regression problems (where the goal is to predict a single numeric value). The ...