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From Pat Ferrel <>
Subject SSVD for dimensional reduction + Kmeans
Date Thu, 09 Aug 2012 23:34:54 GMT
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? 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? I get errors when
I do so trying to figure out if I'm on the wrong track.
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