customizedTraining: Customized Training for Lasso and Elastic-Net Regularized Generalized Linear Models

Customized training is a simple technique for transductive learning, when the test covariates are known at the time of training. The method identifies a subset of the training set to serve as the training set for each of a few identified subsets in the training set. This package implements customized training for the glmnet() and cv.glmnet() functions.

Version: 1.0
Imports: FNN, glmnet
Published: 2016-02-12
Author: Scott Powers, Trevor Hastie, Robert Tibshirani
Maintainer: Scott Powers <sspowers at stanford.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: customizedTraining results

Downloads:

Reference manual: customizedTraining.pdf
Package source: customizedTraining_1.0.tar.gz
Windows binaries: r-devel: customizedTraining_1.0.zip, r-release: customizedTraining_1.0.zip, r-oldrel: customizedTraining_1.0.zip
OS X Snow Leopard binaries: r-release: customizedTraining_1.0.tgz, r-oldrel: not available
OS X Mavericks binaries: r-release: customizedTraining_1.0.tgz