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
