mlpack 3.4.2
nmf_method.hpp
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1
13#ifndef MLPACK_METHODS_CF_DECOMPOSITION_POLICIES_NMF_METHOD_HPP
14#define MLPACK_METHODS_CF_DECOMPOSITION_POLICIES_NMF_METHOD_HPP
15
16#include <mlpack/prereqs.hpp>
21
22namespace mlpack {
23namespace cf {
24
44{
45 public:
57 template<typename MatType>
58 void Apply(const MatType& /* data */,
59 const arma::sp_mat& cleanedData,
60 const size_t rank,
61 const size_t maxIterations,
62 const double minResidue,
63 const bool mit)
64 {
65 if (mit)
66 {
67 amf::MaxIterationTermination iter(maxIterations);
68
69 // Do singular value decomposition using the NMF algorithm.
71 amf::NMFALSUpdate> nmf(iter);
72 nmf.Apply(cleanedData, rank, w, h);
73 }
74 else
75 {
76 amf::SimpleResidueTermination srt(minResidue, maxIterations);
77
78 // Do singular value decomposition using the NMF algorithm.
79 amf::NMFALSFactorizer nmf(srt);
80 nmf.Apply(cleanedData, rank, w, h);
81 }
82 }
83
90 double GetRating(const size_t user, const size_t item) const
91 {
92 double rating = arma::as_scalar(w.row(item) * h.col(user));
93 return rating;
94 }
95
102 void GetRatingOfUser(const size_t user, arma::vec& rating) const
103 {
104 rating = w * h.col(user);
105 }
106
119 template<typename NeighborSearchPolicy>
120 void GetNeighborhood(const arma::Col<size_t>& users,
121 const size_t numUsersForSimilarity,
122 arma::Mat<size_t>& neighborhood,
123 arma::mat& similarities) const
124 {
125 // We want to avoid calculating the full rating matrix, so we will do
126 // nearest neighbor search only on the H matrix, using the observation that
127 // if the rating matrix X = W*H, then d(X.col(i), X.col(j)) = d(W H.col(i),
128 // W H.col(j)). This can be seen as nearest neighbor search on the H
129 // matrix with the Mahalanobis distance where M^{-1} = W^T W. So, we'll
130 // decompose M^{-1} = L L^T (the Cholesky decomposition), and then multiply
131 // H by L^T. Then we can perform nearest neighbor search.
132 arma::mat l = arma::chol(w.t() * w);
133 arma::mat stretchedH = l * h; // Due to the Armadillo API, l is L^T.
134
135 // Temporarily store feature vector of queried users.
136 arma::mat query(stretchedH.n_rows, users.n_elem);
137 // Select feature vectors of queried users.
138 for (size_t i = 0; i < users.n_elem; ++i)
139 query.col(i) = stretchedH.col(users(i));
140
141 NeighborSearchPolicy neighborSearch(stretchedH);
142 neighborSearch.Search(
143 query, numUsersForSimilarity, neighborhood, similarities);
144 }
145
147 const arma::mat& W() const { return w; }
149 const arma::mat& H() const { return h; }
150
154 template<typename Archive>
155 void serialize(Archive& ar, const unsigned int /* version */)
156 {
157 ar & BOOST_SERIALIZATION_NVP(w);
158 ar & BOOST_SERIALIZATION_NVP(h);
159 }
160
161 private:
163 arma::mat w;
165 arma::mat h;
166};
167
168} // namespace cf
169} // namespace mlpack
170
171#endif
This class implements AMF (alternating matrix factorization) on the given matrix V.
Definition: amf.hpp:79
double Apply(const MatType &V, const size_t r, arma::mat &W, arma::mat &H)
Apply Alternating Matrix Factorization to the provided matrix.
This termination policy only terminates when the maximum number of iterations has been reached.
This class implements a method titled 'Alternating Least Squares' described in the following paper:
Definition: nmf_als.hpp:42
This initialization rule for AMF simply fills the W and H matrices with uniform random noise in [0,...
Definition: random_init.hpp:26
This class implements a simple residue-based termination policy.
Implementation of the NMF policy to act as a wrapper when accessing NMF from within CFType.
Definition: nmf_method.hpp:44
double GetRating(const size_t user, const size_t item) const
Return predicted rating given user ID and item ID.
Definition: nmf_method.hpp:90
void GetNeighborhood(const arma::Col< size_t > &users, const size_t numUsersForSimilarity, arma::Mat< size_t > &neighborhood, arma::mat &similarities) const
Get the neighborhood and corresponding similarities for a set of users.
Definition: nmf_method.hpp:120
void Apply(const MatType &, const arma::sp_mat &cleanedData, const size_t rank, const size_t maxIterations, const double minResidue, const bool mit)
Apply Collaborative Filtering to the provided dataset using NMF method.
Definition: nmf_method.hpp:58
const arma::mat & W() const
Get the Item Matrix.
Definition: nmf_method.hpp:147
const arma::mat & H() const
Get the User Matrix.
Definition: nmf_method.hpp:149
void GetRatingOfUser(const size_t user, arma::vec &rating) const
Get predicted ratings for a user.
Definition: nmf_method.hpp:102
void serialize(Archive &ar, const unsigned int)
Serialization.
Definition: nmf_method.hpp:155
Linear algebra utility functions, generally performed on matrices or vectors.
Definition: cv.hpp:1
The core includes that mlpack expects; standard C++ includes and Armadillo.