GenAlgUserEvaluator-class

GenAlgUserEvaluator

Provides a genetic algorithm for finding variable
subsets in high dimensional data with high prediction performance. The
genetic algorithm can use ordinary least squares (OLS) regression models or
partial least squares (PLS) regression models to evaluate the prediction
power of variable subsets. By supporting different cross-validation
schemes, the user can fine-tune the tradeoff between speed and quality of
the solution.

David Kepplinger

gaselect

Genetic Algorithm (GA) for Variable Selection from
High-Dimensional Data

GenAlgUserEvaluator-class function

<dl>
<dt><code>evalFunction</code></dt>
<dd>The function that is called to evaluate the variable subset.</dd></dl>
<dt><code>sepFunction</code></dt>
<dd>The function that calculates the standard error of prediction for the found subsets.</dd>

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User Function Evaluator — GenAlgUserEvaluator-class

<dl>
<dt><code>evalFunction</code></dt>
<dd>The function that is called to evaluate the variable subset.</dd>


<dt><code>sepFunction</code></dt>
<dd>The function that calculates the standard error of prediction for the found subsets.</dd>


</dl>

GenAlgUserEvaluator-class: User Function Evaluator

Description

Arguments

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