Common regression techniques include multiple linear regression, tree-based regression (decision tree, AdaBoost, random forest, bagging), neural network regression, and k-nearest neighbors (k-NN) ...

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

Research on multiple comparison during the past 50 years or so has focused mainly on the comparison of several population means. Several years ago, Spurrier considered the multiple comparison of ...

That might apply to simple things, like predicting the number of college graduates based on the number of college students in any given year. Multiple linear regression.

Abstract Regression interval mapping and multiple interval mapping are compared with regard to mapping linked quantitative trait loci (QTL) in inbred-line cross experiments.

2. Regression of residuals is often used as an alternative to multiple regression, often with the aim of controlling for confounding variables. When correlations exist between independent variables, ...