rd_model

generates a dimension reduction model.

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.

rd_model function

<dl><dt>data</dt>
<dd>dataframe</dd>
<dt>variable.pred</dt>
<dd>the name of the variable to be predicted.</dd>
<dt>mode</dt>
<dd>the method of dimension reduction is defined as mode=1 is the MCP, and mode=0 the ACP.</dd>
<dt>scale</dt>
<dd>the scale parameter of the model.</dd></dl>

Arguments

rd_model — rd_model

<dl>

<dt>data</dt>
<dd>dataframe</dd>


<dt>variable.pred</dt>
<dd>the name of the variable to be predicted.</dd>


<dt>mode</dt>
<dd>the method of dimension reduction is defined as mode=1 is the MCP, and mode=0 the ACP.</dd>


<dt>scale</dt>
<dd>the scale parameter of the model.</dd>

</dl>

rd_model: rd_model

Description

Usage

Arguments

See Also