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questions on optimization and faster processing
I have RapidMiner running on a Xeon quad-code @ 2.67 Ghz, with 12GB Ram on a Win 7 Pro OS.
I am piping in a CSV so I expect the data is all in mem. at this point. I have fed in roughly 20,000 labeled records with around 50 variables. The process is as follows CSV --> Validation ( Bayesian Boost ( W- Ridor) ) --> ( Apply Model + Performance)
I am running the Weka Ridor with a Bay Boost, and Val-X (Apply model/Perfm).
Since I'm looking for the lowest error rate possible I have bumped up the Ridor shuffle to 9, the Bayesian interations to 10, and the number of validations to 10.
I know is somewhat a demanding process but I am finding run times to be slow, going on 23hrs processing. Any tips on how to speed this up? Do these processing time sound reasonable given the process and hardware ?
If there any tips at all, even switching OSs to Linux, etc. I am open to them (as long as its not hardware related)....thanks in advance.