I will choose Mixture Model for the EM implementation. Yifan
2009/4/1 Ted Dunning <ted.dunn...@gmail.com>: > Yifan, > > EM is a highly non-specific term and covers a huge range of very different > algorithms. For example, pLSI, HMM's, and mixture models can all be > estimated using EM. > > What exactly did you mean to address with an EM implementation? > > On Wed, Apr 1, 2009 at 1:05 PM, Grant Ingersoll <gsing...@apache.org> wrote: > >> Hi Yifan, >> >> I think both are good candidates, although AIUI, SVM is a bit harder to >> parallelize, so maybe it would make sense to focus on EM. Of course, we >> don't have to be distributed, so you could propose a non-distributed SVM >> implementation as a first cut and then work on the distributed part as the >> project develops. >> >> ... >>> >>> >>> For EM, it is a generalization of the k-means algorithm, and we already >>> have >>> k-means in the Mahout library. >>> >>> >
