Hi All, Is there a way to compute precision and recall values given a file of recommendations and a test file of user preferences.
I know there is "GenericRecommenderIRStatsEvaluator" in Mahout to compute the IR Stats but it takes a "RecommenderBuilder" object among others as parameters to build a recommender and compute these metrics. However, if I already have a file of recommendations and a test file of preferences, I will not be able to use this class. Another use-case is when my data is temporal i.e I use past data for about a month to train my model and test the recommendations using 1 week future data (backtesting framework). I will not be able to use the above class as it splits the data randomly (I may be wrong in this case). To Summarize, I would like to compute the IR stats for a file of recommendations and a test file of use preferences and would like to know if this can be done using some class in Mahout. Any help is much appreciated. Thanks, Rohit
