title: How mahout's recommendation evaluator works
body: <p>Can anyone tell me how does mahout's RecommenderIRStatsEvaluator work? More specifically how it randomly splits training and testing data and what data the result is compare against? Based on my understating, you need some sort of ideal/expected result which you need to compare against actual result from the recommendation algorithm to find out TP or FP
  and thus compute precision or recall. But it looks like mahout provides a precision/recall score without that ideal/result.   </p>