Package | Description |
---|---|
org.apache.mahout.cf.taste.impl.recommender.svd |
Modifier and Type | Class and Description |
---|---|
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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