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>.
|Author||Myles Lewis [aut, cre] (<https://orcid.org/0000-0001-9365-5345>), Athina Spiliopoulou [aut] (<https://orcid.org/0000-0002-5929-6585>), Katriona Goldmann [aut] (<https://orcid.org/0000-0002-9073-6323>)|
|Maintainer||Myles Lewis <firstname.lastname@example.org>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
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