Package org.mymedialite.itemrec

Provides item recommenders and some helper classes for item recommendation.

See:
          Description

Interface Summary
IIncrementalItemRecommender Interface for item recommenders
 

Class Summary
BPRLinear Linear model optimized for BPR.
BPRMF Matrix factorization model for item prediction (ranking) optimized using BPR.
Extensions Class that contains static methods for item prediction.
IncrementalItemRecommender Base class for item recommenders that support incremental updates.
ItemAttributeKNN k-nearest neighbor item-based collaborative filtering using cosine-similarity over the item attibutes.
ItemKNN Unweighted k-nearest neighbor item-based collaborative filtering using cosine similarity.
ItemRecommender Abstract item recommender class that loads the (positive-only implicit feedback) training data into memory and provides flexible access to it.
KNN Base class for item recommenders that use some kind of kNN model.
MF Abstract class for Matrix Factorization based item predictors.
MostPopular Most-popular item recommender Items are weighted by how often they have been seen in the past.
Perfect Perfect Item Recommender which simply reflects the supplied test results.
Random An Item Recommender which returns random prediction values uniformly distributed between 0.0 and 1.0.
SoftMarginRankingMF Matrix Factorization model for item prediction optimized for a soft margin (hinge) ranking loss, using stochastic gradient descent (as in BPR-MF).
UserAttributeKNN k-nearest neighbor user-based collaborative filtering using cosine-similarity over the user attibutes.
UserKNN k-nearest neighbor user-based collaborative filtering using cosine-similarity (unweighted).
WeightedBPRMF Weighted BPR-MF with frequency-adjusted sampling.
WeightedItemAttributeKNN Weighted k-nearest neighbor item-based collaborative filtering using cosine-similarity over the item attibutes.
WeightedItemHierarchicalAttributeKNN Weighted k-nearest neighbor item-based collaborative filtering using cosine-similarity over the hierarchical item attibutes.
WeightedItemKNN Weighted k-nearest neighbor item-based collaborative filtering using cosine similarity.
WeightedUserKNN Weighted k-nearest neighbor user-based collaborative filtering using cosine-similarity.
Worst Worst possible Item Recommender which reflects the inverse of the supplied test results.
WRMF Weighted matrix factorization method proposed by Hu et al.
Zero Constant item recommender for use as experimental baseline.
 

Package org.mymedialite.itemrec Description

Provides item recommenders and some helper classes for item recommendation.