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From Lance Norskog <goks...@gmail.com>
Subject Re: SVDRecommender convergence?
Date Tue, 31 Aug 2010 22:55:10 GMT
About the SVDRecommender- 10 features and 50 iterations gave
evaluation scores from .70 to .81, solely by changing the random
seeds.

On Tue, Aug 31, 2010 at 12:13 AM, Sean Owen <srowen@gmail.com> wrote:
> I don't have any good rules of thumb for you -- maybe the author can chime in.
> It should be a fairly standard implementation and I would not expect
> unusual behavior in this regard, but can't say I know either way.
>
> But are you asking a question about the recommender or the evaluator?
>
> On Tue, Aug 31, 2010 at 7:35 AM, Lance Norskog <goksron@gmail.com> wrote:
>> Hi-
>>
>> How many features and how many iterations should make the
>> SVDRecommender converge?
>>
>> I used the GroupLens example and 10k dataset with the SVDRecommender
>> instead of the SlopeOneRecommender. The
>> AverageAbsoluteDifferenceRecommenderEvaluator is very sensitive to the
>> random seed. It's on my laptop, so experimenting with # of features
>> and # of iterations got impossible really fast.
>>
>> --
>> Lance Norskog
>> goksron@gmail.com
>>
>



-- 
Lance Norskog
goksron@gmail.com

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