rlr_model

generates a penalized regression 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.

rlr_model function

<dl><dt>data</dt>
<dd>dataframe</dd>
<dt>variable.pred</dt>
<dd>the name of the variable to be predicted.</dd>
<dt>alpha</dt>
<dd>the alpha parameter of the model.</dd>
<dt>standardize</dt>
<dd>the standardize parameter of the model.</dd></dl>

Arguments

rlr_model — rlr_model

<dl>

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


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


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


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

</dl>

rlr_model: rlr_model

Description

Usage

Arguments

See Also