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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: | 1.2 |
Imports: | FNN, glmnet |
Published: | 2019-01-29 |
DOI: | 10.32614/CRAN.package.customizedTraining |
Author: | Scott Powers, Trevor Hastie, Robert Tibshirani |
Maintainer: | Scott Powers <saberpowers at gmail.com> |
License: | GPL-2 |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | customizedTraining results [issues need fixing before 2025-01-10] |
Reference manual: | customizedTraining.pdf |
Package source: | customizedTraining_1.2.tar.gz |
Windows binaries: | r-devel: customizedTraining_1.2.zip, r-release: customizedTraining_1.2.zip, r-oldrel: customizedTraining_1.2.zip |
macOS binaries: | r-release (arm64): customizedTraining_1.2.tgz, r-oldrel (arm64): customizedTraining_1.2.tgz, r-release (x86_64): customizedTraining_1.2.tgz, r-oldrel (x86_64): customizedTraining_1.2.tgz |
Old sources: | customizedTraining archive |
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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.