SERules

Based on Validation tests over BestTivs, a new range of scores is obtained to find new pruned trees.

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

SERules function

<dl><dt>N</dt>
<dd>Number of rows in data.</dd>
<dt>Lv</dt>
<dd>Test set.</dd>
<dt>y</dt>
<dd>Column output indexes in data.</dd>
<dt>fold</dt>
<dd>Parts in which the original data set is divided to perform Cross-Validation.</dd>
<dt>Tk_score</dt>
<dd>Best pruned tree score.</dd>
<dt>BestTivs</dt>
<dd>List of best pruned trees for each training set.</dd></dl>

Arguments

SERules — SERules

<dl>

<dt>N</dt>
<dd>Number of rows in data.</dd>


<dt>Lv</dt>
<dd>Test set.</dd>


<dt>y</dt>
<dd>Column output indexes in data.</dd>


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


<dt>Tk_score</dt>
<dd>Best pruned tree score.</dd>


<dt>BestTivs</dt>
<dd>List of best pruned trees for each training set.</dd>

</dl>

SERules: SERules

Description

Usage

Value

Arguments