kernel_pca.h

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/* MLPACK 0.2
 *
 * Copyright (c) 2008, 2009 Alexander Gray,
 *                          Garry Boyer,
 *                          Ryan Riegel,
 *                          Nikolaos Vasiloglou,
 *                          Dongryeol Lee,
 *                          Chip Mappus, 
 *                          Nishant Mehta,
 *                          Hua Ouyang,
 *                          Parikshit Ram,
 *                          Long Tran,
 *                          Wee Chin Wong
 *
 * Copyright (c) 2008, 2009 Georgia Institute of Technology
 *
 * This program is free software; you can redistribute it and/or
 * modify it under the terms of the GNU General Public License as
 * published by the Free Software Foundation; either version 2 of the
 * License, or (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful, but
 * WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 * General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
 * 02110-1301, USA.
 */
#ifndef KERNEL_PCA_H_
#define KERNEL_PCA_H_

#include <string>
#include <map>
#include <stdio.h>
#include <errno.h>
#include <unistd.h>
#include "fastlib/fastlib.h"
#include "fastlib/la/matrix.h"
#include "fastlib/sparse/sparse_matrix.h"
#include "mlpack/allknn/allknn.h"

class KernelPCATest;
class KernelPCA {
 public:
  friend class KernelPCATest;
  class GaussianKernel {
   public:
    void set(double bandwidth) {
      bandwidth_ = bandwidth;
    }
    double operator()(double distance) {
      return exp(-distance/bandwidth_);
    }
   private:
    double bandwidth_;
  };  
  
  ~KernelPCA() {
    Destruct();
  }
  void Init(std::string data_file, index_t knns, 
      index_t leaf_size);
  void Destruct();
  void ComputeNeighborhoods();
  void LoadAffinityMatrix();
  void EstimateBandwidth(double *bandwidth);
  static void SaveToTextFile(std::string file, 
                             Matrix &eigen_vectors,
                             Vector &eigen_values);
  static void SaveToBinaryFile(std::string file, 
                             Matrix &eigen_vectors,
                             Vector &eigen_values);
  template<typename DISTANCEKERNEL>    
  void ComputeGeneralKernelPCA(DISTANCEKERNEL kernel,
                               index_t num_of_eigenvalues,
                               Matrix *eigen_vectors,
                               Vector *eigen_values);
  void ComputeIsomap(index_t num_of_eigenvalues);
  void ComputeLLE(index_t num_of_eigenvalues,
                  Matrix *eigen_vectors,
                  Vector *eigen_values);
  template<typename DISTANCEKERNEL>
  void ComputeDiffusionMaps(DISTANCEKERNEL kernel, index_t num_of_eigenvalues);
  void ComputeLaplacialnEigenmaps(index_t);
  template<typename DISTANCEKERNEL>
  void ComputeSpectralRegression(DISTANCEKERNEL kernel,
                                 std::map<index_t, index_t> &data_label,
                                 Matrix *embedded_coordinates, 
                                 Vector *eigenvalues);
    
 private:
  AllkNN allknn_;
  index_t knns_;
  Matrix data_;
  SparseMatrix kernel_matrix_;  
  SparseMatrix affinity_matrix_;
  index_t dimension_;
};

#include "kernel_pca_impl.h"
#endif