svd_complete_incremental_learning.hpp

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#ifndef MLPACK_METHODS_AMF_SVD_COMPLETE_INCREMENTAL_LEARNING_HPP
#define MLPACK_METHODS_AMF_SVD_COMPLETE_INCREMENTAL_LEARNING_HPP

#include <mlpack/prereqs.hpp>

namespace mlpack
{
namespace amf
{

template <class MatType>
class SVDCompleteIncrementalLearning
{
 public:
  SVDCompleteIncrementalLearning(double u = 0.0001,
                                 double kw = 0,
                                 double kh = 0)
            : u(u), kw(kw), kh(kh), currentUserIndex(0), currentItemIndex(0)
  {
    // Nothing to do.
  }

  void Initialize(const MatType& /* dataset */, const size_t /* rank */)
  {
    // Initialize the current score counters.
    currentUserIndex = 0;
    currentItemIndex = 0;
  }

  inline void WUpdate(const MatType& V,
                      arma::mat& W,
                      const arma::mat& H)
  {
    arma::mat deltaW;
    deltaW.zeros(1, W.n_cols);

    // Loop until a non-zero entry is found.
    while (true)
    {
      const double val = V(currentItemIndex, currentUserIndex);
      // Update feature vector if current entry is non-zero and break the loop.
      if (val != 0)
      {
        deltaW += (val - arma::dot(W.row(currentItemIndex),
            H.col(currentUserIndex))) * H.col(currentUserIndex).t();

        // Add regularization.
        if (kw != 0)
          deltaW -= kw * W.row(currentItemIndex);
        break;
      }
    }

    W.row(currentItemIndex) += u * deltaW;
  }

  inline void HUpdate(const MatType& V,
                      const arma::mat& W,
                      arma::mat& H)
  {
    arma::mat deltaH;
    deltaH.zeros(H.n_rows, 1);

    const double val = V(currentItemIndex, currentUserIndex);

    // Update H matrix based on the non-zero entry found in WUpdate function.
    deltaH += (val - arma::dot(W.row(currentItemIndex),
        H.col(currentUserIndex))) * W.row(currentItemIndex).t();
    // Add regularization.
    if (kh != 0)
      deltaH -= kh * H.col(currentUserIndex);

    // Move on to the next entry.
    currentUserIndex = currentUserIndex + 1;
    if (currentUserIndex == V.n_rows)
    {
      currentUserIndex = 0;
      currentItemIndex = (currentItemIndex + 1) % V.n_cols;
    }

    H.col(currentUserIndex++) += u * deltaH;
  }

 private:
  double u;
  double kw;
  double kh;

  size_t currentUserIndex;
  size_t currentItemIndex;
};


template<>
class SVDCompleteIncrementalLearning<arma::sp_mat>
{
 public:
  SVDCompleteIncrementalLearning(double u = 0.01,
                                 double kw = 0,
                                 double kh = 0)
            : u(u), kw(kw), kh(kh), n(0), m(0), it(NULL), isStart(false)
    {}

  ~SVDCompleteIncrementalLearning()
  {
    delete it;
  }

  void Initialize(const arma::sp_mat& dataset, const size_t rank)
  {
    (void)rank;
    n = dataset.n_rows;
    m = dataset.n_cols;

    it = new arma::sp_mat::const_iterator(dataset.begin());
    isStart = true;
  }

  inline void WUpdate(const arma::sp_mat& V,
                      arma::mat& W,
                      const arma::mat& H)
  {
    if (!isStart)
        ++(*it);
    else isStart = false;

    if (*it == V.end())
    {
        delete it;
        it = new arma::sp_mat::const_iterator(V.begin());
    }

    size_t currentUserIndex = it->col();
    size_t currentItemIndex = it->row();

    arma::mat deltaW(1, W.n_cols);
    deltaW.zeros();

    deltaW += (**it - arma::dot(W.row(currentItemIndex),
        H.col(currentUserIndex))) * arma::trans(H.col(currentUserIndex));
    if (kw != 0) deltaW -= kw * W.row(currentItemIndex);

    W.row(currentItemIndex) += u*deltaW;
  }

  inline void HUpdate(const arma::sp_mat& /* V */,
                      const arma::mat& W,
                      arma::mat& H)
  {
    arma::mat deltaH(H.n_rows, 1);
    deltaH.zeros();

    size_t currentUserIndex = it->col();
    size_t currentItemIndex = it->row();

    deltaH += (**it - arma::dot(W.row(currentItemIndex),
        H.col(currentUserIndex))) * arma::trans(W.row(currentItemIndex));
    if (kh != 0) deltaH -= kh * H.col(currentUserIndex);

    H.col(currentUserIndex) += u * deltaH;
  }

 private:
  double u;
  double kw;
  double kh;

  size_t n;
  size_t m;

  arma::sp_mat dummy;
  arma::sp_mat::const_iterator* it;

  bool isStart;
}; // class SVDCompleteIncrementalLearning

} // namespace amf
} // namespace mlpack

#endif