Hi, I am a new Mahout user, trying to build my first recommendation engine. I'm using mahout-0.9. My data is boolean -- user, item association without any rating. I am using GenericBooleanPrefUserBasedRecommender with TanimotoCoefficientSimilarity. When I evaluate the recommendation engine with GenericRecommenderIRStatsEvaluator, it starts outputting the evaluation results for each individual user. After the evaluation finishes I run getPrecision() on the return (IRStatistics) and it shows the precision value of the last individual user recommendation precision. Shouldn't it instead return some sort of average of the all individual precision values not the last user value? Also it seems that for all cases precision and recall values are equal, why is that? Is there anything I should do that the evaluation process runs in multithreaded way or is this automatically the case?
Thanks! Hovnatan