class_balance

class_balance.default

class_balance.nestcv.train

Check class balance in training folds

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>.

Myles Lewis

nestedcv

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

Athina Spiliopoulou

Cankut Cubuk

David Rios Santini

Katriona Goldmann

Ryan C. Thompson

class_balance function

<dl><dt>object</dt>
<dd>Object of class <code>nestedcv.glmnet</code>, <code>nestcv.train</code> or <code>outercv</code></dd></dl>

Arguments

Check class balance in training folds — class_balance

<dl>

<dt>object</dt>
<dd>Object of class <code>nestedcv.glmnet</code>, <code>nestcv.train</code> or <code>outercv</code></dd>

</dl>

class_balance: Check class balance in training folds

Description

Usage

Value

Arguments