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CNeighborhoodPreservingEmbedding Class Reference

Detailed Description

NeighborhoodPreservingEmbedding converter used to construct embeddings as described in:

He, X., Cai, D., Yan, S., & Zhang, H.-J. (2005). Neighborhood preserving embedding. Tenth IEEE International Conference on Computer Vision ICCV05 Volume 1, 2, 1208-1213. Ieee. Retrieved from http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1544858

This method is hardly applicable to very high-dimensional data due to necessity to solve eigenproblem involving matrix of size (dim x dim).

Definition at line 38 of file NeighborhoodPreservingEmbedding.h.

Inheritance diagram for CNeighborhoodPreservingEmbedding:
Inheritance graph
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Public Member Functions

 CNeighborhoodPreservingEmbedding ()
 
virtual ~CNeighborhoodPreservingEmbedding ()
 
virtual const char * get_name () const
 
- Public Member Functions inherited from CLocallyLinearEmbedding
 CLocallyLinearEmbedding ()
 
virtual ~CLocallyLinearEmbedding ()
 
virtual CFeaturesapply (CFeatures *features)
 
void set_k (int32_t k)
 
int32_t get_k () const
 
void set_max_k (int32_t max_k)
 
int32_t get_max_k () const
 
void set_auto_k (bool auto_k)
 
bool get_auto_k () const
 
void set_reconstruction_shift (float64_t reconstruction_shift)
 
float64_t get_reconstruction_shift () const
 
void set_nullspace_shift (float64_t nullspace_shift)
 
float64_t get_nullspace_shift () const
 
void set_use_arpack (bool use_arpack)
 
bool get_use_arpack () const
 
- Public Member Functions inherited from CEmbeddingConverter
 CEmbeddingConverter ()
 
virtual ~CEmbeddingConverter ()
 
virtual CSimpleFeatures
< float64_t > * 
embed (CFeatures *features)
 
void set_target_dim (int32_t dim)
 
int32_t get_target_dim () const
 
void set_distance (CDistance *distance)
 
CDistanceget_distance () const
 
void set_kernel (CKernel *kernel)
 
CKernelget_kernel () const
 
- Public Member Functions inherited from CConverter
 CConverter ()
 
virtual ~CConverter ()
 
- Public Member Functions inherited from CSGObject
 CSGObject ()
 
 CSGObject (const CSGObject &orig)
 
virtual ~CSGObject ()
 
virtual bool is_generic (EPrimitiveType *generic) const
 
template<class T >
void set_generic ()
 
void unset_generic ()
 
virtual void print_serializable (const char *prefix="")
 
virtual bool save_serializable (CSerializableFile *file, const char *prefix="")
 
virtual bool load_serializable (CSerializableFile *file, const char *prefix="")
 
void set_global_io (SGIO *io)
 
SGIOget_global_io ()
 
void set_global_parallel (Parallel *parallel)
 
Parallelget_global_parallel ()
 
void set_global_version (Version *version)
 
Versionget_global_version ()
 
SGVector< char * > get_modelsel_names ()
 
char * get_modsel_param_descr (const char *param_name)
 
index_t get_modsel_param_index (const char *param_name)
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 

Protected Member Functions

virtual SGMatrix< float64_tconstruct_embedding (CFeatures *features, SGMatrix< float64_t > matrix, int dimension)
 
- Protected Member Functions inherited from CLocallyLinearEmbedding
void init ()
 HELPERS. More...
 
virtual SGMatrix< float64_tconstruct_weight_matrix (CSimpleFeatures< float64_t > *simple_features, float64_t *W_matrix, SGMatrix< int32_t > neighborhood_matrix)
 
virtual SGMatrix< float64_tconstruct_embedding (SGMatrix< float64_t > matrix, int dimension)
 
virtual SGMatrix< int32_t > get_neighborhood_matrix (SGMatrix< float64_t > distance_matrix, int32_t k)
 
int32_t estimate_k (CSimpleFeatures< float64_t > *simple_features, SGMatrix< int32_t > neighborhood_matrix)
 
float64_t compute_reconstruction_error (int32_t k, int dim, int N, float64_t *feature_matrix, float64_t *z_matrix, float64_t *covariance_matrix, float64_t *resid_vector, float64_t *id_vector, SGMatrix< int32_t > neighborhood_matrix)
 
- Protected Member Functions inherited from CEmbeddingConverter
void init ()
 
- Protected Member Functions inherited from CSGObject
virtual void load_serializable_pre () throw (ShogunException)
 
virtual void load_serializable_post () throw (ShogunException)
 
virtual void save_serializable_pre () throw (ShogunException)
 
virtual void save_serializable_post () throw (ShogunException)
 

Additional Inherited Members

- Public Attributes inherited from CSGObject
SGIOio
 
Parallelparallel
 
Versionversion
 
Parameterm_parameters
 
Parameterm_model_selection_parameters
 
- Static Protected Member Functions inherited from CLocallyLinearEmbedding
static void * run_neighborhood_thread (void *p)
 THREADS. More...
 
static void * run_linearreconstruction_thread (void *p)
 
- Protected Attributes inherited from CLocallyLinearEmbedding
int32_t m_k
 FIELDS. More...
 
int32_t m_max_k
 
float64_t m_reconstruction_shift
 
float64_t m_nullspace_shift
 
bool m_use_arpack
 
bool m_auto_k
 
- Protected Attributes inherited from CEmbeddingConverter
int32_t m_target_dim
 
CDistancem_distance
 
CKernelm_kernel
 

Constructor & Destructor Documentation

constructor

Definition at line 25 of file NeighborhoodPreservingEmbedding.cpp.

destructor

Definition at line 30 of file NeighborhoodPreservingEmbedding.cpp.

Member Function Documentation

SGMatrix< float64_t > construct_embedding ( CFeatures features,
SGMatrix< float64_t matrix,
int  dimension 
)
protectedvirtual

constructs embedding

Parameters
simplefeatures to be used
matrixweight matrix
dimensiondimension of embedding
Returns
null-space approximation feature matrix

Definition at line 39 of file NeighborhoodPreservingEmbedding.cpp.

const char * get_name ( ) const
virtual

get name

Reimplemented from CLocallyLinearEmbedding.

Definition at line 34 of file NeighborhoodPreservingEmbedding.cpp.


The documentation for this class was generated from the following files:

SHOGUN Machine Learning Toolbox - Documentation