#' Classification
#' @export
Classification <- function(dat.all,cls,cl.method,cl.pars,nCores,pw=NULL){
dn <- names(dat.all)
lapply(dn, function(i){
dat <- dat.all[[i]]
cat("\n-Data set = :",i,"\n")
time1 <- FIEmspro:::timer_start()
dat.pair <- dat.sel(dat, cls, choices=pw)
com <- apply(dat.pair$com, 1, paste, collapse="~")
dat.1<- NULL
for (z in 1:length(com)){
dat.com <- data.frame(dat.pair$dat[z],dat.pair$cl[z])
names(dat.com) <- names(dat.pair$dat[[z]])
dat.com <- data.frame(dat.com)
dat.1[z] <- list(dat.com)
}
names(dat.1) <- com
if (nCores <2){
res.cl <- lapply(names(dat.1), function(x,dat) {
cat("\n--Pairwise = :",x); flush.console()
dat <- dat.1[[x]]
runClassification(dat[[x]],cl.method, cl.pars)
},dat=dat.1)
} else {
library(parallel)
clust = makeCluster(nCores, type="PSOCK")
clusterExport(clust,c(ls("package:FIEmspro"),ls("package:MASS"),ls("package:e1071"),ls("package:randomForest"),ls("package:OrbiFIEmisc")))
res.cl <- clusterApplyLB(clust,dat.1,runClassification,cl.method=cl.method,cl.pars=cl.pars)
stopCluster(clust)
}
cat('... done in ',FIEmspro:::timer_end(time1)$dt,"\n",sep=" ")
names(res.cl) <- com
save(res.cl, file=paste(i,"cl_res_DO_NOT_DELETE.RData",sep="_"))
})
aam <- NULL
for (a in 1:length(dn)){
load(file=paste(dn[a],"cl_res_DO_NOT_DELETE.RData",sep="_"))
aam[a] <- list(res.cl)
unlink(paste(dn[a],"cl_res_DO_NOT_DELETE.RData",sep="_"))
}
names(aam) <- dn
aam <- reFormatClassi(aam)
return (aam)
}
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