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
