#include <mlpack/prereqs.hpp>#include <mlpack/methods/amf/update_rules/nmf_mult_dist.hpp>#include <mlpack/methods/amf/update_rules/nmf_als.hpp>#include <mlpack/methods/amf/update_rules/svd_batch_learning.hpp>#include <mlpack/methods/amf/update_rules/svd_incomplete_incremental_learning.hpp>#include <mlpack/methods/amf/update_rules/svd_complete_incremental_learning.hpp>#include <mlpack/methods/amf/init_rules/random_init.hpp>#include <mlpack/methods/amf/init_rules/random_acol_init.hpp>#include <mlpack/methods/amf/termination_policies/simple_residue_termination.hpp>#include <mlpack/methods/amf/termination_policies/simple_tolerance_termination.hpp>#include "amf_impl.hpp"
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Classes | |
| class | mlpack::amf::AMF< TerminationPolicyType, InitializationRuleType, UpdateRuleType > |
| This class implements AMF (alternating matrix factorization) on the given matrix V. More... | |
Namespaces | |
| mlpack | |
| Linear algebra utility functions, generally performed on matrices or vectors. | |
| mlpack::amf | |
| Alternating Matrix Factorization. | |
Typedefs | |
| typedef amf::AMF< amf::SimpleResidueTermination, amf::RandomAcolInitialization<>, amf::NMFALSUpdate > | mlpack::amf::NMFALSFactorizer |
| template<typename MatType = arma::mat> | |
| using | mlpack::amf::SVDBatchFactorizer = amf::AMF< amf::SimpleResidueTermination, amf::RandomAcolInitialization<>, amf::SVDBatchLearning > |
| Convenience typedefs. More... | |
| template<class MatType = arma::mat> | |
| using | mlpack::amf::SVDIncompleteIncrementalFactorizer = amf::AMF< amf::SimpleResidueTermination, amf::RandomAcolInitialization<>, amf::SVDIncompleteIncrementalLearning > |
| SVDIncompleteIncrementalFactorizer factorizes given matrix V into two matrices W and H by incomplete incremental gradient descent. More... | |
| template<class MatType = arma::mat> | |
| using | mlpack::amf::SVDCompleteIncrementalFactorizer = amf::AMF< amf::SimpleResidueTermination, amf::RandomAcolInitialization<>, amf::SVDCompleteIncrementalLearning< MatType > > |
| SVDCompleteIncrementalFactorizer factorizes given matrix V into two matrices W and H by complete incremental gradient descent. More... | |
Detailed Description
Alternating Matrix Factorization
The AMF (alternating matrix factorization) class, from which more commonly known techniques such as incremental SVD, NMF, and batch-learning SVD can be derived.
mlpack is free software; you may redistribute it and/or modify it under the terms of the 3-clause BSD license. You should have received a copy of the 3-clause BSD license along with mlpack. If not, see http://www.opensource.org/licenses/BSD-3-Clause for more information.
