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

Interface Summary

Factorizer	Implementation must be able to create a factorization of a rating matrix
PersistenceStrategy	Provides storage for Factorizations

Class Summary

AbstractFactorizer	base class for Factorizers, provides ID to index mapping
ALSWRFactorizer	factorizes the rating matrix using "Alternating-Least-Squares with Weighted-λ-Regularization" as described in the paper "Large-scale Collaborative Filtering for the Netflix Prize"
ExpectationMaximizationSVDFactorizer	Calculates the SVD using an Expectation Maximization algorithm.
Factorization	a factorization of the rating matrix
FilePersistenceStrategy	Provides a file-based persistent store.
NoPersistenceStrategy	A PersistenceStrategy which does nothing.
SVDRecommender	A Recommender that uses matrix factorization (a projection of users and items onto a feature space)