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

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) ...

A sequential regression or chained equations imputation approach uses a Gibbs sampling-type iterative algorithm that imputes the missing values using a sequence of conditional regression models. It is ...

Using these data, we sought to compare LR against four common ML algorithms: penalized lasso, support vector machine (SVM), k-nearest neighbor (KNN), and random forest (RF) in classification ...