Completing Sean's answer, there are many types of NaNs (multiple different binary representations) -- check out the wikipedia page about it:
http://en.wikipedia.org/wiki/NaN Typically you'll only care about whether a number is a NaN or not (not the kind of NaN). Dawid On Fri, Apr 13, 2012 at 11:51 PM, Sean Owen <[email protected]> wrote: > NaN means "not a number". It is kind of like "null". This means no > answer could be computed, and usually that is because your data is too > sparse. For the kind of recommender you are running, you don't want > such sparse data, and it sounds like you are making the data sparse by > removing a lot of ratings. > > On Thu, Apr 12, 2012 at 10:29 PM, <[email protected]> wrote: >> I have used the UserBasedRecommender to recommend and used the >> AverageAbsoluteDifferenceRecommenderEvaluator as evaluator, when the >> ratings.txt contains more ratings, the evaluator can return some desired >> results, but when i made some requirement about the ratings.txt, for >> example, i filtered out those items that receive more than 4 ratings, the >> evaluator always return NaN. What does NaN mean? It is caused by the >> similarity metric? I have try to pre calculate users' similarity, but it >> returns NaN too. >> what is the problem? >
