scores

This function calculates the score for each pruning of tree_alpha_list.

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

scores function

<dl><dt>N</dt>
<dd>Number of rows in data.</dd>
<dt>Lv_notLv</dt>
<dd>List with train and test sets.</dd>
<dt>x</dt>
<dd>Column input indexes in data.</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>numStop</dt>
<dd>Minimum number of observations on a node to be split.</dd>
<dt>Tk</dt>
<dd>Best pruned tree.</dd>
<dt>tree_alpha_list</dt>
<dd>List with all the possible pruning and its associated alpha.</dd></dl>

Arguments

Pruning Scores — scores

<dl>

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


<dt>Lv_notLv</dt>
<dd>List with train and test sets.</dd>


<dt>x</dt>
<dd>Column input indexes in data.</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>numStop</dt>
<dd>Minimum number of observations on a node to be split.</dd>


<dt>Tk</dt>
<dd>Best pruned tree.</dd>


<dt>tree_alpha_list</dt>
<dd>List with all the possible pruning and its associated alpha.</dd>

</dl>

scores: Pruning Scores

Description

Usage

Value

Arguments