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.

Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

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 ...

Equivariant high-breakdown point regression estimates are computationally expensive, and the corresponding algorithms become unfeasible for moderately large number of regressors. One important advance ...

Learn the difference between linear regression and multiple regression and how investors can use these types of statistical analysis.

Learn how to graph linear regression in Excel. Use these steps to analyze the linear relationship between an independent and a dependent variable.

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 ...