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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 crossvalidation schemes, the user can finetune the tradeoff between speed and quality of the solution.
Package details 


Author  David Kepplinger 
Date of publication  20150212 17:45:27 
Maintainer  David Kepplinger <[email protected]> 
License  GPL (>= 2) 
Version  1.0.5 
Package repository  View on CRAN 
Installation 
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