Subsampling Winner Algorithm 2 for Feature Selection from Large Data

Oregon Convention Center 

The Subsampling Winner Algorithm (SWA, Fan and Sun 2021) provides a novel alternative to penalized methods and random forest procedures. This paper introduces SWA2, the next generation of SWA designed for more general data that may be subject to data heteroskedasticity or interactions. The performance of SWA2 is compared with benchmark methods, including LASSO and SCAD. A new, faster algorithm will be demonstrated through examples.

feature selection

ensemble method

regression

heteroskedasticity

high dimensional data 

Section on Statistical Computing