Interface | Description |
---|---|
Factorizer |
Implementation must be able to create a factorization of a rating matrix
|
PersistenceStrategy |
Provides storage for
Factorization s |
Class | Description |
---|---|
AbstractFactorizer |
base class for
Factorizer s, provides ID to index mapping |
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
|
Factorization |
a factorization of the rating matrix
|
FilePersistenceStrategy |
Provides a file-based persistent store.
|
NoPersistenceStrategy |
A
PersistenceStrategy which does nothing. |
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"
|
ParallelSGDFactorizer.PreferenceShuffler | |
RatingSGDFactorizer |
Matrix factorization with user and item biases for rating prediction, trained with plain vanilla SGD
|
SVDPlusPlusFactorizer |
SVD++, an enhancement of classical matrix factorization for rating prediction.
|
SVDRecommender |
A
Recommender that uses matrix factorization (a projection of users
and items onto a feature space) |
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