## Uses of Class
org.apache.mahout.cf.taste.impl.recommender.svd.AbstractFactorizer

Packages that use AbstractFactorizer
org.apache.mahout.cf.taste.impl.recommender.svd

Uses of AbstractFactorizer in org.apache.mahout.cf.taste.impl.recommender.svd

Subclasses of AbstractFactorizer in org.apache.mahout.cf.taste.impl.recommender.svd
`class` `ALSWRFactorizer` factorizes the rating matrix using "Alternating-Least-Squares with Weighted-λ-Regularization" as described in "Large-scale Collaborative Filtering for the Netflix Prize" also supports the implicit feedback variant of this approach as described in "Collaborative Filtering for Implicit Feedback Datasets" available at http://research.yahoo.com/pub/2433
`class` `ParallelSGDFactorizer` Minimalistic implementation of Parallel SGD factorizer based on "Scalable Collaborative Filtering Approaches for Large Recommender Systems" and "Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent"
`class` `RatingSGDFactorizer` Matrix factorization with user and item biases for rating prediction, trained with plain vanilla SGD
`class` `SVDPlusPlusFactorizer` SVD++, an enhancement of classical matrix factorization for rating prediction.

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