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From Sean Owen <sro...@gmail.com>
Subject Re: R: R: R: Problems with evaluator.
Date Thu, 27 Aug 2009 09:29:13 GMT
Yes, that is correct. The framework splits the user's preferences into
"relevant" and "not relevant" items. It then takes away the relevant
items, and leaves the non-relevant items in the training data. Then,
it sees how many of those relevant items are recommended back to the
user, to compute precision and recall.

On Thu, Aug 27, 2009 at 10:24 AM, Claudia Grieco<grieco@crmpa.unisa.it> wrote:
> Notice this part:
> for (Preference pref : prefs2) {
>        if (!relevantItems.contains(pref.getItem())) {
>          trainingPrefs.add(pref);
>        }}
> It adds a preference only if it's NOT in the relevant items

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