Package org.apache.mahout.cf.taste.impl.recommender

Interface Summary
ClusterSimilarity Returns the "similarity" between two clusters of users, according to some definition of similarity.
TopItems.Estimator<T>  
 

Class Summary
AbstractCandidateItemsStrategy Abstract base implementation for retrieving candidate items to recommend
AbstractRecommender  
AllSimilarItemsCandidateItemsStrategy returns the result of ItemSimilarity.allSimilarItemIDs(long) as candidate items
AllUnknownItemsCandidateItemsStrategy  
ByValueRecommendedItemComparator Defines a natural ordering from most-preferred item (highest value) to least-preferred.
CachingRecommender A Recommender which caches the results from another Recommender in memory.
EstimatedPreferenceCapper Simple class which encapsulates restricting a preference value to a predefined range.
FarthestNeighborClusterSimilarity Defines cluster similarity as the smallest similarity between any two users in the clusters -- that is, it says that clusters are close when all pairs of their members have relatively high similarity.
GenericBooleanPrefItemBasedRecommender A variant on GenericItemBasedRecommender which is appropriate for use when no notion of preference value exists in the data.
GenericBooleanPrefUserBasedRecommender A variant on GenericUserBasedRecommender which is appropriate for use when no notion of preference value exists in the data.
GenericItemBasedRecommender A simple Recommender which uses a given DataModel and ItemSimilarity to produce recommendations.
GenericItemBasedRecommender.MostSimilarEstimator  
GenericRecommendedItem A simple implementation of RecommendedItem.
GenericUserBasedRecommender A simple Recommender which uses a given DataModel and UserNeighborhood to produce recommendations.
ItemAverageRecommender A simple recommender that always estimates preference for an item to be the average of all known preference values for that item.
ItemUserAverageRecommender Like ItemAverageRecommender, except that estimated preferences are adjusted for the users' average preference value.
NearestNeighborClusterSimilarity Defines cluster similarity as the largest similarity between any two users in the clusters -- that is, it says that clusters are close when some pair of their members has high similarity.
NullRescorer<T> A simple Rescorer which always returns the original score.
PreferredItemsNeighborhoodCandidateItemsStrategy  
RandomRecommender Produces random recommendations and preference estimates.
SamplingCandidateItemsStrategy Returns all items that have not been rated by the user (3) and that were preferred by another user (2) that has preferred at least one item (1) that the current user has preferred too.
SimilarUser Simply encapsulates a user and a similarity value.
TopItems A simple class that refactors the "find top N things" logic that is used in several places.
TreeClusteringRecommender A Recommender that clusters users, then determines the clusters' top recommendations.
TreeClusteringRecommender2 A Recommender that clusters users, then determines the clusters' top recommendations.
 



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