Implements nested k*l-fold cross-validation for lasso and elastic-net regularised linear models via the 'glmnet' package and other machine learning models via the 'caret' package <doi:10.1093/bioadv/vbad048>. Cross-validation of 'glmnet' alpha mixing parameter and embedded fast filter functions for feature selection are provided. Described as double cross-validation by Stone (1977) <doi:10.1111/j.2517-6161.1977.tb01603.x>. Also implemented is a method using outer CV to measure unbiased model performance metrics when fitting Bayesian linear and logistic regression shrinkage models using the horseshoe prior over parameters to encourage a sparse model as described by Piironen & Vehtari (2017) <doi:10.1214/17-EJS1337SI>.
| Version: | 0.8.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | caret,data.table,doParallel,foreach,future.apply,ggplot2,glmnet,matrixStats,matrixTests, methods, parallel,pROC,Rfast,RhpcBLASctl,rlang,ROCR |
| Suggests: | Boruta,CORElearn,fastshap (≥ 0.1.0),gbm,ggbeeswarm,ggpubr,hsstan,mda,mlbench,pbapply,pls,randomForest,ranger,RcppEigen,rmarkdown,knitr,SuperLearner |
| Published: | 2025-03-10 |
| DOI: | 10.32614/CRAN.package.nestedcv |
| Author: | Myles Lewis [aut, cre], Athina Spiliopoulou [aut], Cankut Cubuk [ctb], Katriona Goldmann [ctb], Ryan C. Thompson [ctb] |
| Maintainer: | Myles Lewis <myles.lewis at qmul.ac.uk> |
| BugReports: | https://github.com/myles-lewis/nestedcv/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/myles-lewis/nestedcv |
| NeedsCompilation: | no |
| Language: | en-gb |
| Citation: | nestedcv citation info |
| Materials: | README,NEWS |
| In views: | MachineLearning |
| CRAN checks: | nestedcv results |