CRAN/E | nestedcv

nestedcv

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

Installation

About

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.

Citation nestedcv citation info
github.com/myles-lewis/nestedcv
Bug report File report

Key Metrics

Version 0.7.8
Published 2024-03-13 47 days ago
Needs compilation? no
License MIT
License File
CRAN checks nestedcv results
Language en-gb

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Maintainer

Maintainer

Myles Lewis

myles.lewis@qmul.ac.uk

Authors

Myles Lewis

aut / cre

Athina Spiliopoulou

aut

Cankut Cubuk

ctb

Katriona Goldmann

ctb

Material

README
NEWS
Reference manual
Package source

In Views

MachineLearning

Vignettes

nestedcv guide
Using outercv with Bayesian shrinkage models
Explaining nestedcv models with Shapley values

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

nestedcv archive

Imports

caret
data.table
doParallel
foreach
ggplot2
glmnet
matrixStats
matrixTests
methods
parallel
pROC
Rfast
RhpcBLASctl
rlang
ROCR

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