nestedcv: Nested Cross-Validation with 'glmnet' and 'caret'

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. 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>.

Package details

AuthorMyles Lewis [aut, cre] (<>), Athina Spiliopoulou [aut] (<>), Katriona Goldmann [aut] (<>)
MaintainerMyles Lewis <>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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nestedcv documentation built on Sept. 11, 2022, 1:06 a.m.