Class | Description |
---|---|
ConstantGuessRecommender |
Baseline: predict by a constant rating
|
GlobalAverageRecommender |
Baseline: predict by average rating of all users
|
ItemAverageRecommender |
Baseline: predict by the average of target item's ratings
|
ItemClusterRecommender |
It is a graphical model that clusters items into K groups for recommendation, as opposite to
the
UserCluster recommender. |
MostPopularRecommender |
Baseline: items are weighted by the number of ratings they received.
|
RandomGuessRecommender |
Baseline: predict by a random value in (minRate, maxRate)
|
UserAverageRecommender |
Baseline: predict by the average of target user's ratings
|
UserClusterRecommender |
It is a graphical model that clusters users into K groups for recommendation, see reference: Barbieri et al.,
Probabilistic Approaches to Recommendations (Section 2.2), Synthesis Lectures on Data Mining and
Knowledge Discovery, 2014.
|
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