Learn R Programming

mogavs (version 1.1.0)

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 data sets with large number of variables. For more information, see Sinha, Malo & Kuosmanen (2015) .

Copy Link

Version

Install

install.packages('mogavs')

Monthly Downloads

159

Version

1.1.0

License

GPL-2

Maintainer

Tommi Pajala

Last Published

January 26th, 2018

Functions in mogavs (1.1.0)

cv.mogavs

k-Fold Crossvalidation for a mogavs model
getBestModel

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

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

Simulated Data Set for MOGA-VS
createAdditionalPlots

Function for plotting boundaries of the archive set.
crimeData

Crime Data Set with Imputed Values
getBestModelVars

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

Package for regression variable selection with genetic algorithm MOGA-VS
mogavs

Multiobjective Genetic Algorithm for Variable Selection
mogavsToLinear

Transform a mogavs model into a linear model.
summary.mogavs

Summary function for mogavs