That sounds like old code then, not the latest version. In fact I am pretty sure you are right that in older code (probably 0.1) it wasn't doing what I say.
Update to the latest SVN code, or, keep your eyes peeled for 0.2 which should be released any day now. On Tue, Nov 3, 2009 at 1:46 PM, James James <[email protected]> wrote: > Hi, Thanks for the reply. In fact, the code I quote comes from the class > BooleanUserGenericUserBasedRecommender. I do not know if that is what you > refer to as GenericBooleanPrefBasedRecommender. I could not find a class by > the name GenericBooleanPrefBasedRecommender under > org.apache.mahout.cf.taste.impl.recommender. > > Thanks again. > > > > > ________________________________ > From: Sean Owen <[email protected]> > To: [email protected] > Sent: Tue, November 3, 2009 1:13:39 AM > Subject: Re: recommender on binary data > > Not sure if I ever asked on this thread: are you using > GenericBooleanPrefUserBasedRecommender? this is the class that alters > GenericUserBasedRecommender with this abused notion of estimated > preference. The code you quote is not from > GenericBooleanPrefUserBasedRecommender. > > On Tue, Nov 3, 2009 at 2:50 AM, James James <[email protected]> > wrote: >> It has been a while since we talked about this topic, but the score returned >> is not just adding up the similarity values that anybody in the neighborhood >> has to the item. IT is atucally devided by the totalSimilarity. As result, I >> think the score is still 1.0. Did I miss something? See the codes below. >> for(User user : theNeighborhood) {if(!user.equals(theUser)) {// See >> GenericItemBasedRecommender.doEstimatePreference() tooPreference pref = >> user.getPreferenceFor(itemID); >> preference += theSimilarity * pref.getValue(); >> totalSimilarity += theSimilarity; >> } >> } >> } >> } >> > > > >
