.cv.glmnet

Wrapper for <code>cv.glmnet</code>,
with different handling of sparsity constraints.

Implements stacked elastic net regression (Rauschenberger 2021, <doi:10.1093/bioinformatics/btaa535>). The elastic net generalises ridge and lasso regularisation (Zou 2005, <doi:10.1111/j.1467-9868.2005.00503.x>). Instead of fixing or tuning the mixing parameter alpha, we combine multiple alpha by stacked generalisation (Wolpert 1992 <doi:10.1016/S0893-6080(05)80023-1>).

Armin Rauschenberger

starnet

Stacked Elastic Net

.cv.glmnet function

<dl><dt>...</dt>
<dd>see <code>cv.glmnet</code></dd>
<dt>nzero</dt>
<dd>maximum number of non-zero coefficients:
positive integer</dd></dl>

Arguments

glmnet::cv.glmnet — .cv.glmnet

<dl>

<dt>...</dt>
<dd>see <code>cv.glmnet</code></dd>


<dt>nzero</dt>
<dd>maximum number of non-zero coefficients:
positive integer</dd>

</dl>

.cv.glmnet: glmnet::cv.glmnet

Description

Usage

Value

Arguments

Examples