Hello, When testing the mahout example BookCrossingRecommender with default settings (GenericUserBasedRecommender, PearsonCorrelationSimilarity, NearestNUserNeighborhood), I noticed that the result of the evaluation (AverageAbsoluteDifferenceRecommenderEvaluator) are changing randomly, from one test to another. I get scores between 2.1 and 4.8.
Considering the size of the input (about 100000 users and 100000 books), I can't imagine that the randomness in the algorithms can lead to huge evaluation differences like that. What do you think?
