amf.hpp

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#ifndef MLPACK_METHODS_AMF_AMF_HPP
#define MLPACK_METHODS_AMF_AMF_HPP

#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>

namespace mlpack {
namespace amf  {

template<typename TerminationPolicyType = SimpleResidueTermination,
         typename InitializationRuleType = RandomAcolInitialization<>,
         typename UpdateRuleType = NMFMultiplicativeDistanceUpdate>
class AMF
{
 public:
  AMF(const TerminationPolicyType& terminationPolicy = TerminationPolicyType(),
      const InitializationRuleType& initializeRule = InitializationRuleType(),
      const UpdateRuleType& update = UpdateRuleType());

  template<typename MatType>
  double Apply(const MatType& V,
               const size_t r,
               arma::mat& W,
               arma::mat& H);

  const TerminationPolicyType& TerminationPolicy() const
  { return terminationPolicy; }
  TerminationPolicyType& TerminationPolicy() { return terminationPolicy; }

  const InitializationRuleType& InitializeRule() const
  { return initializationRule; }
  InitializationRuleType& InitializeRule() { return initializationRule; }

  const UpdateRuleType& Update() const { return update; }
  UpdateRuleType& Update() { return update; }

 private:
  TerminationPolicyType terminationPolicy;
  InitializationRuleType initializationRule;
  UpdateRuleType update;
}; // class AMF

typedef amf::AMF<amf::SimpleResidueTermination,
                 amf::RandomAcolInitialization<>,
                 amf::NMFALSUpdate> NMFALSFactorizer;

#ifdef MLPACK_USE_CXX11

template<class MatType>
using SVDBatchFactorizer = amf::AMF<amf::SimpleResidueTermination,
                                    amf::RandomAcolInitialization<>,
                                    amf::SVDBatchLearning>;

template<class MatType>
using SVDIncompleteIncrementalFactorizer = amf::AMF<
    amf::SimpleResidueTermination,
    amf::RandomAcolInitialization<>,
    amf::SVDIncompleteIncrementalLearning>;
template<class MatType>
using SVDCompleteIncrementalFactorizer = amf::AMF<
    amf::SimpleResidueTermination,
    amf::RandomAcolInitialization<>,
    amf::SVDCompleteIncrementalLearning<MatType>>;

#else // #ifdef MLPACK_USE_CXX11

typedef amf::AMF<amf::SimpleResidueTermination,
                 amf::RandomAcolInitialization<>,
                 amf::SVDBatchLearning> SparseSVDBatchFactorizer;

typedef amf::AMF<amf::SimpleResidueTermination,
                 amf::RandomAcolInitialization<>,
                 amf::SVDBatchLearning> SVDBatchFactorizer;
typedef amf::AMF<amf::SimpleResidueTermination,
                 amf::RandomAcolInitialization<>,
                 amf::SVDIncompleteIncrementalLearning>
        SparseSVDIncompleteIncrementalFactorizer;

typedef amf::AMF<amf::SimpleResidueTermination,
                 amf::RandomAcolInitialization<>,
                 amf::SVDIncompleteIncrementalLearning>
        SVDIncompleteIncrementalFactorizer;

typedef amf::AMF<amf::SimpleResidueTermination,
                 amf::RandomAcolInitialization<>,
                 amf::SVDCompleteIncrementalLearning<arma::sp_mat> >
        SparseSVDCompleteIncrementalFactorizer;

typedef amf::AMF<amf::SimpleResidueTermination,
                 amf::RandomAcolInitialization<>,
                 amf::SVDCompleteIncrementalLearning<arma::mat> >
        SVDCompleteIncrementalFactorizer;

#endif // #ifdef MLPACK_USE_CXX11

} // namespace amf
} // namespace mlpack

// Include implementation.
#include "amf_impl.hpp"

#endif // MLPACK_METHODS_AMF_AMF_HPP