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
