Hey Sean, are you talking about using GenericRecommenderIRStatsEvaluator/CHOOSE_THRESHOLD? I am already using that. I have however bumped up the training size, maybe this will help.
- Matt On Sat, Jul 14, 2012 at 3:13 AM, Sean Owen <sro...@gmail.com> wrote: > It still means the same thing. 220K lines may still be too sparse to > get results. Also try removing your threshold and let it pick. > > On Sat, Jul 14, 2012 at 3:24 AM, Matt Mitchell <goodie...@gmail.com> wrote: >> Hmm, still happening. I have a 220k line file with user, item and pref >> value. I am still getting the NaN error when evaluating. I'm not sure >> what to do. It also takes a long time for this error to popup, around >> 1 hour. I hate to throw code out like this, but maybe it'll be help >> someone... help me. Is it related to the evaluator settings? >> >> - Matt >> >> (def prefs-file "data.txt") >> (org.apache.mahout.common.RandomUtils/useTestSeed) >> (let [model (FileDataModel. (File. prefs-file)) >> evaluator (GenericRecommenderIRStatsEvaluator.) >> rbuilder (reify RecommenderBuilder >> (buildRecommender [this model] >> (let [sim (LogLikelihoodSimilarity. model)] >> (GenericBooleanPrefItemBasedRecommender. model sim)))) >> mbuilder (reify DataModelBuilder >> (buildDataModel [this training-data] >> (GenericBooleanPrefDataModel. >> (GenericBooleanPrefDataModel/toDataMap >> training-data))))] >> (prn (.evaluate evaluator rbuilder mbuilder model nil 10 >> GenericRecommenderIRStatsEvaluator/CHOOSE_THRESHOLD >> 0.01))) >> >> >> On Sat, Jul 7, 2012 at 11:20 AM, Matt Mitchell <goodie...@gmail.com> wrote: >>> Thanks Sean, you're absolutely right. Things are working nicely now. >>> >>> - Matt >>> >>> On Sat, Jul 7, 2012 at 3:48 AM, Sean Owen <sro...@gmail.com> wrote: >>>> What it really means is that there is not enough data to make a >>>> meaningful test here. >>>> >>>> On Sat, Jul 7, 2012 at 1:28 AM, Matt Mitchell <goodie...@gmail.com> wrote: >>>>> Hi, >>>>> >>>>> I have a recommender, with a boolean prefs model. I am following the >>>>> instructions in the MIA book, but only get this exception: >>>>> >>>>> Illegal precision: NaN >>>>> [Thrown class java.lang.IllegalArgumentException] >>>>> >>>>> Restarts: >>>>> 0: [QUIT] Quit to the SLIME top level >>>>> >>>>> Backtrace: >>>>> 0: >>>>> com.google.common.base.Preconditions.checkArgument(Preconditions.java:88) >>>>> 1: >>>>> org.apache.mahout.cf.taste.impl.eval.IRStatisticsImpl.<init>(IRStatisticsImpl.java:35) >>>>> 2: >>>>> org.apache.mahout.cf.taste.impl.eval.GenericRecommenderIRStatsEvaluator.evaluate(GenericRecommenderIRStatsEvaluator.java:212) >>>>> >>>>> The code is written in Clojure, I hope that's OK: >>>>> >>>>> (let [model (GenericBooleanPrefDataModel. >>>>> (GenericBooleanPrefDataModel/toDataMap >>>>> (FileDataModel. (File. "resources/test.data")))) >>>>> evaluator (GenericRecommenderIRStatsEvaluator.) >>>>> rbuilder (reify RecommenderBuilder >>>>> (buildRecommender [this model] >>>>> (let [sim (LogLikelihoodSimilarity. model) >>>>> nhood (NearestNUserNeighborhood. 10 sim model)] >>>>> (GenericBooleanPrefUserBasedRecommender. model >>>>> nhood sim)))) >>>>> mbuilder (reify DataModelBuilder >>>>> (buildDataModel [this training-data] >>>>> (GenericBooleanPrefDataModel. >>>>> (GenericBooleanPrefDataModel/toDataMap >>>>> training-data))))] >>>>> (.evaluate evaluator rbuilder mbuilder model nil 10 >>>>> GenericRecommenderIRStatsEvaluator/CHOOSE_THRESHOLD >>>>> 1.0)) >>>>> >>>>> My test data file is very simple (for now): >>>>> >>>>> 1,1 >>>>> 1,2 >>>>> 1,3 >>>>> >>>>> 2,1 >>>>> 2,10 >>>>> 2,100 >>>>> 2,20 >>>>> >>>>> 3,9 >>>>> 3,10 >>>>> 3,20 >>>>> 3,1 >>>>> >>>>> 4,10 >>>>> 4,15 >>>>> 4,1 >>>>> >>>>> Any idea what I might be doing wrong? >>>>> >>>>> Thanks in advance, >>>>> >>>>> - Matt
