nestedcv: Nested Cross-Validation with 'glmnet' and 'caret' (original) (raw)
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 |
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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 |
Maintainer: | Myles Lewis <myles.lewis at qmul.ac.uk> |
BugReports: | https://github.com/myles-lewis/nestedcv/issues |
License: | MIT + file |
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 |
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