Multiobjective Genetic Algorithm for Variable Selection in Regression
Function for plotting boundaries of the archive set.
k-Fold Crossvalidation for a mogavs model
Get the best model with nvar variables, or by AIC, BIC or knee-point.
Get variable names of the best model with nvar variables, or defined b...
Package for regression variable selection with genetic algorithm MOGA-...
Multiobjective Genetic Algorithm for Variable Selection
Transform a mogavs model into a linear model.
Produce a visual summary of how many times each variable appears on th...
Summary function for mogavs
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) <doi:10.1080/10618600.2014.899236>.