foreach - R parallel computing inconsistent results -


i trying speed r script using parallel processing since computationally demanding.

after research , testing, have (i think !) got working. however, output different every time run foreach loop on exact same data. doing wrong ?

cl <- makecluster(detectcores()-2)

registerdosnow(cl)

x <- foreach(i = 1:35, .combine = "c") %dopar% {

my code ...

return(percentageerror)}

inside code body doing machine learning on data set, , returning percentage error.

my returned percentageerror result different every time run code.

what ideally result of each loop iteration stored, , once loop has finished, calculate mean of stored results.


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