mtry_inputSelection

This function randomly selects the variables that are evaluated to divide a node and removes those that do not present variability.

Functions are provided to determine production frontiers and technical
efficiency measures through non-parametric techniques based upon regression trees.
The package includes code for estimating radial input, output, directional and
additive measures, plotting graphical representations of the scores and the production
frontiers by means of trees, and determining rankings of importance of input variables
in the analysis. Additionally, an adaptation of Random Forest by a set of individual
Efficiency Analysis Trees for estimating technical efficiency is also included. More
details in: <doi:10.1016/j.eswa.2020.113783>.

Miriam Esteve

Efficiency Analysis Trees

Víctor España

Juan Aparicio

Xavier Barber

mtry_inputSelection function

<dl><dt>data</dt>
<dd><code>data.frame</code> containing the training set.</dd>
<dt>x</dt>
<dd>Column input indexes in data.</dd>
<dt>t</dt>
<dd>Node which is being split.</dd>
<dt>mtry</dt>
<dd>Number of inputs selected for a node to be split.</dd></dl>

Arguments

Random Selection of Variables — mtry_inputSelection

<dl>

<dt>data</dt>
<dd><code>data.frame</code> containing the training set.</dd>


<dt>x</dt>
<dd>Column input indexes in data.</dd>


<dt>t</dt>
<dd>Node which is being split.</dd>


<dt>mtry</dt>
<dd>Number of inputs selected for a node to be split.</dd>

</dl>

mtry_inputSelection: Random Selection of Variables

Description

Usage

Value

Arguments