############################# CentClass_Pred is a function that models response classes using centroid classification approach consideting pearson correlation as measure of similarity between samples
############################# Input variables of this function are as follows:
############################# 1) TrainFeat: Feature frame (rows as samples and columns as features) for training set
############################# 2) TrainObs: Observed classess for training
############################# 3) TestFeat: Feature frame (rows as samples and columns as features) for testing
CentClass_Pred <- function(TrainFeat, TrainObs, TestFeat){
ClassName <- unique(TrainObs)
############
ClassAveMat <- c()
for(ClassIter in 1:length(ClassName)){
ClassMatchInd <- which(TrainObs == ClassName[ClassIter])
ClassAveMat <- rbind(ClassAveMat, apply(TrainFeat[ClassMatchInd,], 2, median))
}
############
PredVal <- c()
for(TestSamIter in 1:nrow(TestFeat)){
SimCor <- unlist(lapply(1:nrow(ClassAveMat), function(Iter){cor.test(as.numeric(ClassAveMat[Iter,]),
as.numeric(TestFeat[TestSamIter,]),
method = "s")$estimate}))
PredVal <- c(PredVal, ClassName[which(SimCor == max(SimCor))[
sample.int(length(which(SimCor == max(SimCor))),1)]])
}
############
return(PredVal)
}
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