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 + file LICENSE 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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=nestedcv to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4