There are many different techniques available to create a regression model. Some common techniques, listed from less complex to more complex, are: linear regression, linear lasso regression, linear ...

We propose covariance-regularized regression, a family of methods for prediction in high dimensional settings that uses a shrunken estimate of the inverse covariance matrix of the features to achieve ...

The literature of ridge regression and James-Stein estimation is broadly reviewed, and critical comments are interpolated on a number of papers. The authors also express their viewpoints on ridge ...

This article explains how to create and use kernel ridge regression (KRR) models. Compared to other regression techniques, KRR is especially useful when there is limited training data. There are ...