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STPGA (version 2.0)

Selection of Training Populations by Genetic Algorithm

Description

Can be utilized to select a test data calibrated training population in high dimensional prediction problems and assumes that the explanatory variables are observed for all of the individuals. Once a "good" training set is identified, the response variable can be obtained only for this set to build a model for predicting the response in the test set.

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Version

Install

install.packages('STPGA')

Monthly Downloads

175

Version

2.0

License

GPL-3

Maintainer

Deniz Akdemir

Last Published

May 5th, 2016

Functions in STPGA (2.0)

AOPT

AOPT
CDMAX0

CDMAX0
GenAlgForSubsetSelectionNoTest

Genetic algorithm for subset selection no given test
CDMAX2

CDMAX2
PEVMAX2

PEVMAX2
PEVMAX0

PEVMAX0
STPGA-package

Selection of Training Populations by Genetic Algorithm
makeonecross

Make a cross from two solutions and mutate.
CDMAX

CDMAX
GenerateCrossesfromElites

Generate crosses from elites
PEVMEAN2

PEVMEAN2
PEVMAX

PEVMAX
CDMEAN0

CDMEAN0
CDMEAN

CDMEAN
PEVMEAN0

PEVMEAN0
CDMEAN2

CDMEAN2
DOPT

DOPT
PEVMEAN

PEVMEAN
GenAlgForSubsetSelection

Genetic algorithm for subset selection