You can easily implement an uncentered cosine similarity metric. If
you have reasons to do this I'd be curious to hear -- are there
practical reasons for it?
my problem is that using Person correlation with adjusted weighed
average prediction (i.e. not shifting the weights) results in a very bad
RMSE, especially for item-based (but I get a surprisingly good results
for other measures), so that surely something wrong with negative weights.
however, just tried cosine similarity and EuclideanDistanceSimilarity
for item-based, they are OK in terms of RMSE (around 1.03 for both),
although EuclideanDistanceSimilarity performs a slightly better with
other measures ( e.g. NDCG, MAP, precision, etc).
T
