Well, yes VW is an appealing option but I only found "experimental" integrations so far.
Also, early experiments suggest Decision Trees Ensembles (RF, GBT) perform better than generalized linear models on our data. Hence the interest for MLLib :) Any other comments / suggestions welcome :) E/ 2014-06-19 12:37 GMT+02:00 Charles Earl <charles.ce...@gmail.com>: > While I can't definitively speak to MLLib online learning, > I'm sure you're evaluating Vowpal Wabbit, for which there's been some > storm integrations contributed. > Also you might look at factorie, http://factorie.cs.understanding.edu, > which at least provides an online lda. > C > > > On Thursday, June 19, 2014, Eustache DIEMERT <eusta...@diemert.fr> wrote: > >> Hi Sparkers, >> >> We have a Storm cluster and looking for a decent execution engine for >> machine learned models. What I've seen from MLLib is extremely positive, >> but we can't just throw away our Storm based stack. >> >> So my question is: is it feasible/recommended to train models in >> Spark/MLLib and execute them in another Java environment (Storm in this >> case) ? >> >> Thanks for any insights :) >> >> Eustache >> > > > -- > - Charles >
