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#-----------------------------------------------------------------------------#
# #
# GENERALIZED NETWORK-BASED DIMENSIONALITY REDUCTION AND ANALYSIS (GNDA) #
# #
# Written by: Zsolt T. Kosztyan*, Marcell T. Kurbucz, Attila I. Katona, #
# Zahid Khan #
# *Department of Quantitative Methods #
# University of Pannonia, Hungary #
# kosztyan.zsolt@gtk.uni-pannon.hu #
# #
# Last modified: February 2024 #
#-----------------------------------------------------------------------------#
######### Feature selection for KMO #######
#' @export
fs.KMO<-function(data,min_MSA=0.5,cor.mtx=FALSE){
if (!requireNamespace("psych", quietly = TRUE)) {
stop(
"Package \"psych\" must be installed to use this function.",
call. = FALSE
)
}
if (is.data.frame(data)|is.matrix(data)){
if (ncol(data)>=2){
x<-data
loop=TRUE
while(loop==TRUE){
kmo<-psych::KMO(x)
if (min(kmo$MSAi)>min_MSA){loop=FALSE}else{
i<-which.min(kmo$MSAi)
if (cor.mtx==TRUE){
x<-x[-i,-i]
}else{
x<-x[,-i]
}
}
if (ncol(x)<2){
loop=FALSE
}
}
return(x)
}else{
stop("Error: data must contain at least 2 columns!")
step.KMO<-NULL
return(step.KMO)
}
}else{
stop("Error: data must be a matrix or a dataframe!")
step.KMO<-NULL
return(step.KMO)
}
}
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