check_remove_var

internal

An interface to build machine learning models for
classification and regression problems. 'mikropml' implements the ML
pipeline described by Topçuoğlu et al. (2020)
<doi:10.1128/mBio.00434-20> with reasonable default options for data
preprocessing, hyperparameter tuning, cross-validation, testing, model
evaluation, and interpretation steps. See the website
<https://www.schlosslab.org/mikropml/> for more information,
documentation, and examples.

Kelly Sovacool

mikropml

User-Friendly R Package for Supervised Machine Learning
Pipelines

Begüm Topçuoğlu

Zena Lapp

Evan Snitkin

Jenna Wiens

Patrick Schloss

Nick Lesniak

Courtney Armour

Sarah Lucas

check_remove_var function

<dl><dt>remove_var</dt>
<dd>Whether to remove variables with near-zero variance
(<code>'nzv'</code>; default), zero variance (<code>'zv'</code>), or none (<code>NULL</code>).</dd></dl>

Arguments

Zena Lapp, <a href="/link/zenalapp%40umich.edu?package=mikropml&version=1.6.1" data-mini-rdoc="mikropml::zenalapp@umich.edu">zenalapp@umich.edu</a>

Author

Check remove_var — check_remove_var

<dl>

<dt>remove_var</dt>
<dd>Whether to remove variables with near-zero variance
(<code>'nzv'</code>; default), zero variance (<code>'zv'</code>), or none (<code>NULL</code>).</dd>

</dl>

Zena Lapp, <a href='mailto:zenalapp@umich.edu'>zenalapp@umich.edu</a>

check_remove_var: Check remove_var

Description

Usage

Arguments

Author

Examples