plot.vim

This function plots variable importance measures yielded by the function
<code>vim</code> in a dotchart.

A statistical learning method that tries to find the best set
of predictors and interactions between predictors for modeling binary or
quantitative response data in a decision tree. Several search algorithms
and ensembling techniques are implemented allowing for finetuning the
method to the specific problem. Interactions with quantitative
covariables can be properly taken into account by fitting local
regression models. Moreover, a variable importance measure for assessing
marginal and interaction effects is provided. Implements the
procedures proposed by Lau et al. (2024, <doi:10.1007/s10994-023-06488-6>).

Michael Lau

logicDT

Identifying Interactions Between Binary Predictors

plot.vim function

<dl><dt>x</dt>
<dd>An object of the class <code>vim</code></dd>
<dt>p</dt>
<dd>The number of most important terms which will be included
in the plot. A value of 0 leads to plotting all terms.</dd>
<dt>...</dt>
<dd>Ignored additional parameters</dd></dl>

Arguments

Plot calculated VIMs — plot.vim

<dl>

<dt>x</dt>
<dd>An object of the class <code>vim</code></dd>


<dt>p</dt>
<dd>The number of most important terms which will be included
in the plot. A value of 0 leads to plotting all terms.</dd>


<dt>...</dt>
<dd>Ignored additional parameters</dd>

</dl>

plot.vim: Plot calculated VIMs

Description

Usage

Value

Arguments