boosting_prediction

model

test.data

number of trees used in the prediction.

n.trees

generates the prediction of a boosting 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

Oldemar Rodriguez R.

Andres Navarro D.

Diego Jimenez A.

Ariel Arroyo S.

boosting_prediction function

<dl><dt>model</dt>
<dd>boosting model(gbm).</dd>
<dt>test.data</dt>
<dd>dataframe.</dd>
<dt>n.trees</dt>
<dd>number of trees used in the prediction.</dd></dl>

Arguments

boosting_prediction — boosting_prediction

<dl>

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


<dt>test.data</dt>
<dd>dataframe.</dd>


<dt>n.trees</dt>
<dd>number of trees used in the prediction.</dd>

</dl>

boosting_prediction: boosting_prediction

Description

Usage

Arguments

See Also