Learn R Programming
⚠️There's a newer version (1.1.0) of this package.Take me there.

mogavs (version 1.0.1)

Multiobjective Genetic Algorithm for Variable Selection in Regression

Description

Functions for exploring the best subsets in regression with a genetic algorithm. The package is much faster than methods relying on complete enumeration, and is suitable for datasets with large number of variables.

Copy Link

Version

Install

install.packages('mogavs')

Monthly Downloads

20

Version

1.0.1

License

GPL-2

Maintainer

Tommi Pajala

Last Published

November 6th, 2015

Functions in mogavs (1.0.1)

getBestModelVars

Get variable names of the best model with nvar variables, or defined by lowest MSE, AIC, BIC or knee-point.
createAdditionalPlots

Function for plotting boundaries of the archive set.
plotVarUsage

Produce a visual summary of how many times each variable appears on the efficient frontier.
mogavsToLinear

Transform a mogavs model into a linear model.
mogavs

Multiobjective Genetic Algorithm for Variable Selection
cv.mogavs

k-Fold Crossvalidation for a mogavs model
summary.mogavs

Summary function for mogavs
getBestModel

Get the best model with nvar variables, or by AIC, BIC or knee-point.
crimeData

Crime Data Set with Imputed Values
sampleData

Simulated Data Set for MOGA-VS
mogavs-package

Package for regression variable selection with genetic algorithm MOGA-VS