Uses of Interface
org.apache.mahout.cf.taste.impl.recommender.ClusterSimilarity

Packages that use ClusterSimilarity

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

Uses of ClusterSimilarity in org.apache.mahout.cf.taste.impl.recommender

Classes in org.apache.mahout.cf.taste.impl.recommender that implement ClusterSimilarity

class	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.
class	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.

Constructors in org.apache.mahout.cf.taste.impl.recommender with parameters of type ClusterSimilarity

TreeClusteringRecommender(DataModel dataModel, ClusterSimilarity clusterSimilarity, double clusteringThreshold)

TreeClusteringRecommender(DataModel dataModel, ClusterSimilarity clusterSimilarity, double clusteringThreshold, double samplingRate)

TreeClusteringRecommender(DataModel dataModel, ClusterSimilarity clusterSimilarity, int numClusters)

TreeClusteringRecommender(DataModel dataModel, ClusterSimilarity clusterSimilarity, int numClusters, double samplingRate)

TreeClusteringRecommender2(DataModel dataModel, ClusterSimilarity clusterSimilarity, double clusteringThreshold)

TreeClusteringRecommender2(DataModel dataModel, ClusterSimilarity clusterSimilarity, int numClusters)