l0 {cbl}

Feature selection subroutine

Description

This function fits a potentially sparse supervised learning model and returns a bit vector indicating which features were selected.

Usage

l0(x, y, s, params, ...)

Arguments

x

Design matrix.

y

Outcome vector.

s

Regression method. Current options are "lasso" or "boost".

params

Optional list of parameters to use when s = "boost".

...

Extra parameters to be passed to the feature selection subroutine.