plot_RMSE

graph the root mean square error of cross validation according to components used.

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.

plot_RMSE function

<dl><dt>model</dt>
<dd>a dimension reduction model.</dd>
<dt>n.comp</dt>
<dd>the optimum number of components.</dd>
<dt>titles</dt>
<dd>labels on the chart</dd></dl>

Arguments

Ariel Arroyo &lt;luis.ariel.arroyo@promidat.com&gt;

Author

plot_RMSE — plot_RMSE

<dl>

<dt>model</dt>
<dd>a dimension reduction model.</dd>


<dt>n.comp</dt>
<dd>the optimum number of components.</dd>


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

</dl>

plot_RMSE: plot_RMSE

Description

Usage

Value

Arguments

Author