CRAN/E | STPGA

STPGA

Selection of Training Populations by Genetic Algorithm

Installation

About

Combining Predictive Analytics and Experimental Design to Optimize Results. To 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. The algorithms in the package can be tweaked to solve some other subset selection problems.

Key Metrics

Version 5.2.1
R ≥ 2.10
Published 2018-11-24 1588 days ago
Needs compilation? no
License GPL-3
CRAN checks STPGA results

Downloads

Last 24 hours 0 -100%
Last 7 days 69 -49%
Last 30 days 336 +50%
Last 90 days 761 +9%
Last 365 days 3.472 -32%

Maintainer

Maintainer

Deniz Akdemir

deniz.akdemir.work@gmail.com

Authors

Deniz Akdemir

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

STPGA archive

Depends

R ≥ 2.10
AlgDesign
scales
scatterplot3d
emoa
grDevices

Suggests

R.rsp
EMMREML
quadprog
UsingR
glmnet
leaps
Matrix