I wanted to ask about the problem of deciding to treat 0.0 as a null value or a valid number in the Mahout recommenders. Basically, Mahout treats 0.0 as the null value for ratings, probably because this is compatible with the sparse vector representations (most obviously with RandomAccessSparseVector). But in principle, there is no reason why 0.0 should not be a valid rating, and the null value should be represented by "null". Have other folks come up against this problem, and if so, how have they solved it? Modifying RandomAccessSparseVector looks like a lot of work. I could just add n to all of my ratings so that min(rating+n) > 0 and then subtract n from the predicted ratings, but that's really, really ugly. Does anyone have a better idea? Thanks.
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