Package: customizedTraining 1.3
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.
Authors:
customizedTraining_1.3.tar.gz
customizedTraining_1.3.zip(r-4.7-any)customizedTraining_1.3.zip(r-4.6-any)customizedTraining_1.3.zip(r-4.5-any)
customizedTraining_1.3.tgz(r-4.6-any)customizedTraining_1.3.tgz(r-4.5-any)
customizedTraining_1.3.tar.gz(r-4.7-any)customizedTraining_1.3.tar.gz(r-4.6-any)
customizedTraining_1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
customizedTraining/json (API)
| # Install 'customizedTraining' in R: |
| install.packages('customizedTraining', repos = c('https://saberpowers.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/saberpowers/customizedtraining/issues
- Vowel - Vowel Recognition
Last updated from:edb4170a20. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 111 | ||
| source / vignettes | OK | 115 | ||
| linux-release | OK | 121 | ||
| macos-release | OK | 179 | ||
| macos-oldrel | OK | 189 | ||
| windows-devel | OK | 75 | ||
| windows-release | OK | 59 | ||
| windows-oldrel | OK | 59 | ||
| wasm-release | OK | 95 |
Exports:customizedGlmnetcv.customizedGlmnetnonzero
Dependencies:codetoolsFNNforeachglmnetiteratorslatticeMatrixRcppRcppEigenshapesurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Fit glmnet using customized training | customizedGlmnet |
| Cross validation for customizedGlmnet | cv.customizedGlmnet |
| Return selected variables | nonzero |
| Return selected variables from a 'customizedGlmnet' object | nonzero.customizedGlmnet |
| Return selected variables from a 'singleton' object | nonzero.singleton |
| Visualize variables selected in each customized training subset | plot.customizedGlmnet |
| Visualize variables selected in each customized training subset, from a cross-validated model | plot.cv.customizedGlmnet |
| Make predictions from a 'customizedGlmnet' object | predict.customizedGlmnet |
| Make predictions from a 'cv.customizedGlmnet' object | predict.cv.customizedGlmnet |
| Make predictions from a ``singleton'' object | predict.singleton |
| Print the summary of a fitted 'customizedGlmnet' object | print.customizedGlmnet |
| Print a ``cv.customizedGlmnet'' object | print.cv.customizedGlmnet |
| Vowel Recognition | Vowel |