[R] classification for huge datasets: SVM yields memory troubles
christoph.lehmann at gmx.ch
Mon Dec 13 13:27:11 CET 2004
I have a matrix with 30 observations and roughly 30000 variables, each
obs belongs to one of two groups. With svm and slda I get into memory
troubles ('cannot allocate vector of size' roughly 2G). PCA LDA runs
fine. Are there any way to use the memory issue withe SVM's? Or can you
recommend any other classification method for such huge datasets?
P.S. I run suse 9.1 on a 2G RAM PIV machine.
thanks for a hint
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