Reading "overview and usage" doc linked on that page https://cwiki.apache.org/confluence/display/MAHOUT/Stochastic+Singular+Value+Decomposition should help to clarify outputs and usage.
On Thu, Aug 9, 2012 at 4:44 PM, Dmitriy Lyubimov <[email protected]> wrote: > On Thu, Aug 9, 2012 at 4:34 PM, Pat Ferrel <[email protected]> wrote: >> Quoth Grant Ingersoll: >>> To put this in bin/mahout speak, this would look like, munging some names >>> and taking liberties with the actual argument to be passed in: >>> >>> bin/mahout svd (original -> svdOut) >>> bin/mahout cleansvd ... >>> bin/mahout transpose svdOut -> svdT >>> bin/mahout transpose original -> originalT >>> bin/mahout matrixmult originalT svdT -> newMatrix >>> bin/mahout kmeans newMatrix >> >> I'm trying to create a test case from testKmeansDSVD2 to use SSVDSolver. >> Does SSVD require the EigenVerificationJob to clean the eigen vectors? > > No > >> if so where does SSVD put the equivalent of >> DistributedLanczosSolver.RAW_EIGENVECTORS? Seems like they should be in V* >> but SSVD creates V so should I transpose V* then run it through the >> EigenVerificationJob? > no > > SSVD is SVD, meaning it produces U and V with no further need to clean that > >> I get errors when I do so trying to figure out if I'm on the wrong track.
