The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
Fits a univariate-guided sparse regression (lasso), by a two-stage
procedure. The first stage fits p separate univariate models to the
response. The second stage gives more weight to the more important
univariate features, and preserves their signs. Conveniently, it returns
an objects that inherits from class glmnet, so that all of
the methods for glmnet are available. See doi:10.48550/arXiv.2501.18360 for details.
To install the uniLasso R package directly from github, run the following in R:
library(devtools)
install_github(repo="trevorhastie/uniLasso")These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.