rlr_type

returns the name of the penalty according to the alpha.

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_type function

<dl><dt>alpha_rlr</dt>
<dd>the penalty is defined as alpha=1 is the lasso penalty, and alpha=0 the ridge penalty.</dd></dl>

Arguments

rlr_type — rlr_type

<dl>

<dt>alpha_rlr</dt>
<dd>the penalty is defined as alpha=1 is the lasso penalty, and alpha=0 the ridge penalty.</dd>

</dl>

rlr_type: rlr_type

Description

Usage

Arguments

See Also

Examples