But since I'm using boolean preference data, all the preferences are relevant
(score 1) so they are all erased from the training data:
for (Preference pref : prefs) {
if (pref.getValue() >= theRelevanceThreshold) {
relevantItems.add(pref.getItem());
}
}
-----Messaggio originale-----
Da: Sean Owen [mailto:[email protected]]
Inviato: giovedì 27 agosto 2009 11.29
A: [email protected]
Oggetto: Re: R: R: R: Problems with evaluator.
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<[email protected]> 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
