For this size a dense solver like in commons math should work. For larger sizes (up to about a million non-zeros), the in-memory stochastic projection SVD in Mahout should work well.
On Thu, Jul 5, 2012 at 12:44 AM, Sean Owen <[email protected]> wrote: > If you want Java, the implementation in Commons Math is just fine. > There are others. > > Limiting the number of features is just a matter of tossing all but > the first k rows, or columns. > > On Thu, Jul 5, 2012 at 9:46 AM, Lance Norskog <[email protected]> wrote: > > What is a good factorizer for doing low-grade LSA? This would be for > > small term-vector sets and document summarization. For example, a few > > hundred sentences v.s. a thousand words. This would be apache > > licensed. I stole the Mahout SVD implementation, but wonder if there > > is a better alternative. The Mahout implementation does not support > > limiting the number of features (singular values). > > > > -- > > Lance Norskog > > [email protected] >
