sodavis: SODA: Main and Interaction Effects Selection for Discriminant Analysis and Logistic Regression

Variable and interaction selection are essential to classification in high-dimensional setting. In this package, we provide the implementation of SODA procedure, which is a forward-backward algorithm that selects both main and interaction effects under quadratic discriminant analysis and logistic regression model.

Version: 0.1
Depends: R (≥ 3.0.0), nnet, MASS
Published: 2015-11-16
Author: Yang Li, Jun S. Liu
Maintainer: Yang Li <yli01 at>
License: GPL-2
NeedsCompilation: no
CRAN checks: sodavis results


Reference manual: sodavis.pdf
Package source: sodavis_0.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: not available, r-oldrel: not available
OS X Mavericks binaries: r-release: sodavis_0.1.tgz