We are building PredictionIO that helps to handle a number of business logics. Recommending only items that the user has never expressed a preference before is supported. It is a layer on top of Mahout. Hope it is helpful.
Simon On Wed, Jul 31, 2013 at 4:57 PM, Ted Dunning <[email protected]> wrote: > Go with 0.8. Definitely. > > Hadoop scaleout should be easy. > > > On Wed, Jul 31, 2013 at 4:19 PM, Rafal Lukawiecki < > [email protected]> wrote: > > > Thank you! > > > > In general, should I be putting our efforts into using 0.8 or stick with > > 0.7 for now, re RecommenderJob? > > > > On another note, which might be a different thread, but would you have > any > > ready-made accuracy and reliability validation code to suggest when using > > RecommenderJob, or do I need to stick with predicting from test data/test > > partitions, and analysing resulting confusion matrices in R etc? Anything > > turnkey aides to entice new users. > > > > Rafal > > > > Ps. Another reason for using RJ in our use case is the hopeful, assumed > > promise of a Hadoop-derived scale-out, when needed in the near future. > > Mixed results so far on that end. > > -- > > Rafal Lukawiecki > > Pardon my brevity, sent from a telephone. > > > > On 1 Aug 2013, at 00:09, "Ted Dunning" <[email protected]> wrote: > > > > > On Wed, Jul 31, 2013 at 4:06 PM, Rafal Lukawiecki < > > > [email protected]> wrote: > > > > > >> Many thanks, I'll report the issue, when I figure out where. :) > > > > > > I can help with that! > > > > > > https://issues.apache.org/jira/browse/MAHOUT > > >
