On Wed, Sep 4, 2013 at 11:43 AM, Ted Dunning <[email protected]> wrote: > On Wed, Sep 4, 2013 at 10:59 AM, Dmitriy Lyubimov <[email protected]> wrote: > >> > Now, what happens in the case of SVD? >> > The vectors are normal by definition. >> > Are singular values used at all, or just left and right singular vectors? >> >> SVD does not take weights so it cannot ignore or weigh out a >> non-observation, which is why it is not well suited for matrix >> completion problem per se >> > > There are multiple ways to read the use of weights here. > > In the original posting, I think the gist was how to treat the singular > values, not how to weight different observations. Mahout's SSVD allows the > singular values to be kept separate, to be applied entirely to the left or > right singular values or to be split across both in a square root sort of > way.
>From solely SSVD point of view, it depends on what is requested. Yes one could compute three separate outputs, which is the default, or outputs that bake in singular values to either side, or square roots of singular values to either side. (I never used the latter myself, but in papers it is mentioned as a means to build useful similarities between document and a term in LSA case).
