Mahout ssvd usage

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I am trying to use mahout's stochastic svd algorithm on a small dataset to compare it with the regular svd algorithm (DistributedLanczos).

I built the covariance matrix for the dataset and I feed it to mahout svd which returns a cleaneigenvectors file with the eigenvectors of this covariance matrix.

How can I compute the equivalent of cleaneigenvectors with mahout ssvd?

mahout ssvd produces 3 folders with the 3 matrices of the svd decomposition (U, V and Sigma). Is the file in V folder equivalent to cleaneigenvectors?

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