Hi Sean Actually, i even find something more interesting from book "Mahout in Action" in Chapter 6 Page 72, "Note that the values in R do not represent an estimated preference value -- they’re far too large, for one. These could be normalized into estimated preference values with some additional computation, if desired. But for purposes here, normalization doesn’t matter, since the ordering of recommendations is the important thing, not the exact values on which the ordering depends." The value R is the estimated result computed by running org.apache.mahout.cf.taste.hadoop.item.RecommenderJob, can i use it directly to do the compartion? The book says the R can be normalized into estimated pref, i'm not sure it has been done or not by the RecommenderJob? ThanksRamon
> Date: Mon, 17 Oct 2011 17:26:37 +0100 > Subject: Re: Does Mahout provide a way to evaluate a distributed Recommender > running on Hadoop? > From: [email protected] > To: [email protected] > > Yes that's actually probably a easy and quick way to get what you want. > > 2011/10/17 WangRamon <[email protected]>: > > > > Hi Sean > > It seems in order to get the estimated pref values for compartion in a > > distributed environment, i have to complete run > > org.apache.mahout.cf.taste.hadoop.item.RecommenderJob, meanwhile, set a > > bigger value to "recommendationsPerUser" to make sure my test data can > > exist in the estimated top items. Do i miss something? Any idea? Thanks in > > advance. > > CheersRamon > >
