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From Zia mel <ziad.kame...@gmail.com>
Subject Re: Precision question
Date Mon, 28 Jan 2013 17:17:18 GMT
Any thoughts of this ?

On Sat, Jan 26, 2013 at 10:55 AM, Zia mel <ziad.kamel25@gmail.com> wrote:
> OK , in the precison when we reduce the size of sample to .1 or 0.05 ,
> would the results be related when we check with all the data ? For
> example, if we have data1 and data2 and test them using 0.1 and found
> that data 1 is producing better results , would the same thing stand
> when we check with all data?
>
>  IRStatistics stats = evaluator.evaluate(recommenderBuilder,
>                                             null, model, null, 10,
>
> GenericRecommenderIRStatsEvaluator.CHOOSE_THRESHOLD,
>                                             0.05);
>
> Many thanks
>
> On Fri, Jan 25, 2013 at 12:26 PM, Sean Owen <srowen@gmail.com> wrote:
>> No, it takes a fixed "at" value. You can modify it to do whatever you want.
>> You will see it doesn't bother with users with little data, like <
>> 2*at data points.
>>
>> On Fri, Jan 25, 2013 at 6:23 PM, Zia mel <ziad.kamel25@gmail.com> wrote:
>>> Interesting. Using
>>>  IRStatistics stats = evaluator.evaluate(recommenderBuilder,
>>>                                             null, model, null, 5,
>>>
>>> GenericRecommenderIRStatsEvaluator.CHOOSE_THRESHOLD,
>>>                                             1.0);
>>>
>>> Can it be adjusted to each user ? In other words, is there a way to
>>> select a threshold instead of using 5 ?  mm Something like selecting y
>>> set , each set have a min of z user ?
>>>
>>>
>>>
>>> On Fri, Jan 25, 2013 at 12:09 PM, Sean Owen <srowen@gmail.com> wrote:
>>>> The way I do it is to set x different for each user, to the number of
>>>> items in the user's test set -- you ask for x recommendations.
>>>> This makes precision == recall, note. It dodges this problem though.
>>>>
>>>> Otherwise, if you fix x, the condition you need is stronger, really:
>>>> each user needs >= x *test set* items in addition to training set
>>>> items to make this test fair.
>>>>
>>>>
>>>> On Fri, Jan 25, 2013 at 4:10 PM, Zia mel <ziad.kamel25@gmail.com> wrote:
>>>>> When selecting precision at x let's say 5 , should I check that all
>>>>> users have 5 items or more? For example, if a user have 3 items and
>>>>> they were removed as top items,  then how can the recommender suggest
>>>>> items since there are no items to learn from?
>>>>> Thanks !

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