mrIML_bird_parasites_RF

<p><div class="sourceCode"></div></p><pre><code>data &lt;- MRFcov::Bird.parasites
Y &lt;- data %&gt;%
  dplyr::select(-scale.prop.zos) %&gt;%
  dplyr::select(order(everything()))
X &lt;- data %&gt;%
  dplyr::select(scale.prop.zos)
</code></pre><p></p>

datasets

Builds and interprets multi-response machine learning models using 'tidymodels' syntax. Users can supply a tidy model, and 'mrIML' automates the process of fitting multiple response models to multivariate data and applying interpretable machine learning techniques across them. For more details see Fountain-Jones (2021) <doi:10.1111/1755-0998.13495> and Fountain-Jones et al. (2024) <doi:10.22541/au.172676147.77148600/v1>.

Nick Fountain-Jones

mrIML

Multi-Response (Multivariate) Interpretable Machine Learning

Ryan Leadbetter

Gustavo Machado

Chris Kozakiewicz

Nick Clark

mrIML_bird_parasites_RF function

<p>An object of class <code>list</code> of length 3.</p>

Format

<p><div class="sourceCode"></p><pre><code>data &lt;- MRFcov::Bird.parasites
Y &lt;- data %&gt;%
  dplyr::select(-scale.prop.zos) %&gt;%
  dplyr::select(order(everything()))
X &lt;- data %&gt;%
  dplyr::select(scale.prop.zos)
</code></pre><p></div></p>

mrIML_bird_parasites_RF: An example mrIML model fit to MRFcov::Bird.parasites

Description

Usage

Arguments

Format

Details