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cvRFBORUTA <- function(logX, groupings, DIR, params=NULL) {
#list(seed=123, ncv=5, repeats=10,maxRuns=300, rfimportance="MeanDecreaseGini", ntree=1000, localImp=TRUE, fs.method="rf_boruta", savres=FALSE)) {
if(is.null(params)) {
params <- control_params()
}
fs.method <- params$fs.method #"rf_boruta"
seed <- params$seed
ncv <- params$ncv
repeats <- params$repeats
maxRuns <- params$maxRuns
jitter <- params$jitter
rfimportance <- params$rfimportance
ntree <- params$ntree
fs.method <- params$fs.method
localImp <- params$localImp
saveres <- params$saveres
## introduce some minimal noise to make scaling etc. possible
if(jitter) {
logX <- jitter(logX)
}
## create an output folder if results should be saved
if(saveres & !is.null(DIR)) {
SUBDIR <- paste(DIR,fs.method,sep="/")
if(!file.exists(SUBDIR))
dir.create(SUBDIR)
fnames <- paste(SUBDIR, "/", names(groupings), ".pdf", sep="")
} else {
SUBDIR <- NULL
fnames <- rep("-", length(groupings)) #paste(names(groupings), ".pdf", sep="")
}
X <- lapply(1:length(groupings), function(i,groupings,fnames) list(groupings[[i]], fnames[i]), groupings=groupings, fnames=fnames)
names(X) <- names(groupings)
## use multicores if more than one group is to be classified
useparallel <- length(grep("package:(parallel|multicore)", search())>0)
if(length(X)>1 & useparallel) {
resRF <- mclapply(X, cv_rfclass, logX=logX, ncv=ncv, repeats=repeats, seed=seed, maxRuns=maxRuns, rfimportance=rfimportance, ntree=ntree, fs.method=fs.method, localImp=localImp, mc.preschedule=TRUE, mc.cores=length(X))
} else {
resRF <- lapply(X, cv_rfclass, logX=logX, ncv=ncv, repeats=repeats, seed=seed, maxRuns=maxRuns, rfimportance=rfimportance, ntree=ntree, fs.method=fs.method, localImp=localImp)
}
#rrr <- rfclass_cv(X[["groupings"]], logX=logX, ncv=ncv, repeats=repeats, seed=seed, maxRuns=maxRuns)
#resRF <- list(ttype=rrr)
## extract the performance objects
performance <- lapply(resRF, function(x) x$performance)
names(performance) <- names(X)
## is this really needed? should probably not be written without asking...
featlist <- extract_features_rf_boruta(resRF, SUBDIR)
if(saveres & !is.null(SUBDIR)) {
save(resRF, X, logX, fs.method, rfimportance, ntree, localImp, SUBDIR, featlist, file=paste(SUBDIR, "env.RData", sep="/"))
}
list(res=resRF, featlist=featlist, performance=performance)
}
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