PS I just fixed a bug that might cause the problem you see. It resulted in an infinite loop in some cases, and I could imagine that it only came up when data sets get a little larger. try the latest from subversion to see if it helps.
On Thu, Aug 13, 2009 at 8:03 PM, mishkinf<[email protected]> wrote: > > I have been using mahout-0.1 release version and I am able to get > recommendations with datasets roughly 5 million and under but when I attempt > 10 million or so no recommendations are given to me. Has anybody had this > problem? I'm not sure if I am just using the wrong recommender > settings/recommender or if I should just switch to trunk version or > something. Ideas? Suggestions? > > I have tried item-item recommender, user-item recommenders.... nearest > neighborhood... tree clustering.. > They all produce numerous recommendations with the smaller data sets. In > theory it should only get better with a larger data set. > > Currently I'm using item-item recommender with caching item similarities and > cashing recommender.. > > ItemSimilarity similarity = new PearsonCorrelationSimilarity(dataModel); > CachingItemSimilarity cis = new CachingItemSimilarity(similarity, > dataModel); > recommender = new CachingRecommender(new > GenericItemBasedRecommender(dataModel, similarity)); > > ...... > > I would like to have Mahout to work with 25-50 million rows of data but as > of yet 5 million is the best i can do. RAM has also been an issue with > larger data sets. > -- > View this message in context: > http://www.nabble.com/Mahout-not-giving-recommendations-with-large-data-sets-tp24956912p24956912.html > Sent from the Mahout User List mailing list archive at Nabble.com. > >
