Package: customizedTraining 1.2
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_1.2.tar.gz
customizedTraining_1.2.zip(r-4.5)customizedTraining_1.2.zip(r-4.4)customizedTraining_1.2.zip(r-4.3)
customizedTraining_1.2.tgz(r-4.4-any)customizedTraining_1.2.tgz(r-4.3-any)
customizedTraining_1.2.tar.gz(r-4.5-noble)customizedTraining_1.2.tar.gz(r-4.4-noble)
customizedTraining_1.2.tgz(r-4.4-emscripten)customizedTraining_1.2.tgz(r-4.3-emscripten)
customizedTraining.pdf |customizedTraining.html✨
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 6 years agofrom:8feae96962. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 05 2024 |
| R-4.5-win | OK | Nov 05 2024 |
| R-4.5-linux | OK | Nov 05 2024 |
| R-4.4-win | OK | Nov 05 2024 |
| R-4.4-mac | OK | Nov 05 2024 |
| R-4.3-win | OK | Nov 05 2024 |
| R-4.3-mac | OK | Nov 05 2024 |
Exports:customizedGlmnetcv.customizedGlmnetnonzerononzero.customizedGlmnetnonzero.singletonplot.customizedGlmnetplot.cv.customizedGlmnetpredict.customizedGlmnetpredict.cv.customizedGlmnetpredict.singletonprint.customizedGlmnetprint.cv.customizedGlmnet
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 |
