Variable selection, also known as feature screening, is getting much attention in many research areas, especially for large ‘omics data sets. This workshop will introduce why we should do variable selection and some basic variable selection methods including stepwise, forward and backward regression. The Least absolute shrinkage and selection operator (LASSO) method will also be covered as a widely used variable selection method. Furthermore, this workshop will include the elastic net method, which is a combination of the ridge regression and the LASSO method. All the methods will be implemented in R.

 Outline:

1. Why use variable selection?
2. Stepwise forward and backward regression
3. The LASSO method
4. The Elastic Net in R