boosting_importance_plot

generates the graph of variable importance.

Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.

Oldemar Rodriguez

regressoR

Regression Data Analysis System

Diego Jimenez A.

boosting_importance_plot function

<dl><dt>model</dt>
<dd>boosting model(gbm).</dd>
<dt>titles</dt>
<dd>Labels on the chart</dd></dl>

Arguments

boosting_importance_plot — boosting_importance_plot

<dl>

<dt>model</dt>
<dd>boosting model(gbm).</dd>


<dt>titles</dt>
<dd>Labels on the chart</dd>

</dl>

boosting_importance_plot: boosting_importance_plot

Description

Usage

Arguments