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?
