/usr/include/shogun/converter/LaplacianEigenmaps.h is in libshogun-dev 1.1.0-4ubuntu2.
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* 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 3 of the License, or
* (at your option) any later version.
*
* Written (W) 2011 Sergey Lisitsyn
* Copyright (C) 2011 Berlin Institute of Technology and Max-Planck-Society
*/
#ifndef LAPLACIANEIGENMAPS_H_
#define LAPLACIANEIGENMAPS_H_
#include <shogun/lib/config.h>
#ifdef HAVE_LAPACK
#include <shogun/converter/EmbeddingConverter.h>
#include <shogun/features/Features.h>
#include <shogun/distance/Distance.h>
namespace shogun
{
class CFeatures;
class CDistance;
/** @brief the class LaplacianEigenmaps used to preprocess
* data using Laplacian Eigenmaps algorithm as described in:
*
* Belkin, M., & Niyogi, P. (2002).
* Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering.
* Science, 14, 585-591. MIT Press.
* Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.19.9400&rep=rep1&type=pdf
*
* Note that the algorithm is very sensitive to the heat distribution coefficient
* and number of neighbors in the nearest neighbor graph. No connectivity check
* is provided, so the preprocessor will not produce reasonable embeddings if the k value
* makes a graph that is not connected.
*
* This implementation is not parallel due to performance issues. Generalized
* eigenproblem is the bottleneck for this algorithm.
*
* Solving of generalized eigenproblem involves LAPACK DSYGVX routine
* and requires extra memory for right-hand side matrix storage.
* If ARPACK is available then DSAUPD/DSEUPD is used with no extra
* memory usage.
*
*/
class CLaplacianEigenmaps: public CEmbeddingConverter
{
public:
/** constructor */
CLaplacianEigenmaps();
/** destructor */
virtual ~CLaplacianEigenmaps();
/** apply to features
* @param features to embed
* @param embedding features
*/
virtual CFeatures* apply(CFeatures* features);
/** embed distance
* @param distance to use for embedding
* @param embedding features
*/
virtual CSimpleFeatures<float64_t>* embed_distance(CDistance* distance, CFeatures* features=NULL);
/** setter for K parameter
* @param k k value
*/
void set_k(int32_t k);
/** getter for K parameter
* @return k value
*/
int32_t get_k() const;
/** setter for TAU parameter
* @param tau tau value
*/
void set_tau(float64_t tau);
/** getter for TAU parameter
* @return tau value
*/
float64_t get_tau() const;
/** get name */
virtual const char* get_name() const;
protected:
/** init */
void init();
/** construct embedding
* @param features features
* @param W_matrix W matrix to be used
*/
virtual CSimpleFeatures<float64_t>* construct_embedding(CFeatures* features,
SGMatrix<float64_t> W_matrix);
protected:
/** number of neighbors */
int32_t m_k;
/** tau parameter of heat distribution */
float64_t m_tau;
};
}
#endif /* HAVE_LAPACK */
#endif /* LAPLACIANEIGENMAPS_H_ */
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