generateLv

This function splits the original data in two new data sets: a train set and a test set.

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

generateLv function

<dl><dt>data</dt>
<dd>Data to be split into train and test subsets.</dd>
<dt>fold</dt>
<dd>Parts in which the original set is divided, to perform Cross-Validation.</dd></dl>

Arguments

Train and Test Sets Generation — generateLv

<dl>

<dt>data</dt>
<dd>Data to be split into train and test subsets.</dd>


<dt>fold</dt>
<dd>Parts in which the original set is divided, to perform Cross-Validation.</dd>

</dl>

generateLv: Train and Test Sets Generation

Description

Usage

Value

Arguments