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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 |
| 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 |
| 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.