GClasses::GScalingUnfolder Class Reference

Detailed Description

This is a nonlinear dimensionality reduction algorithm loosely inspired by Maximum Variance Unfolding. It iteratively scales up the data, then restores distances between neighbors.

#include <GManifold.h>

Inheritance diagram for GClasses::GScalingUnfolder:

Public Member Functions
	GScalingUnfolder ()
	GScalingUnfolder (GDomNode *pNode)
virtual	~GScalingUnfolder ()
GRand &	rand ()
	Returns a reference to the pseudo-random number generator used by this object. More...
virtual GMatrix *	reduce (const GMatrix &in)
	Reduces the dimensionality of "in". More...
void	setNeighborCount (size_t n)
	Specify the number of neighbors to use. (The default is 14.) More...
void	setPasses (size_t n)
	Specify the number of times to 'scale the data then recover local relationships'. More...
void	setRefinesPerScale (size_t n)
	Specify the number of times to refine the points after each scaling. More...
void	setScaleRate (double d)
	Specify the scaling rate. The default is 0.9. More...
void	setTargetDims (size_t n)
	Specify the number of dimensions in the output results. More...
void	unfold (GMatrix &intrinsic, GNeighborGraph &nf, size_t encoderTrainIters=0, GNeuralNetLearner *pEncoder=NULL, GNeuralNetLearner *pDecoder=NULL, const GMatrix *pVisible=NULL)
	Unfolds the points in intrinsic, such that distances specified in nf are preserved. If pVisible is non-NULL, then pEncoder will be incrementally trained to encode pVisible to intrinsic. More...
Public Member Functions inherited from GClasses::GTransform
	GTransform ()
	GTransform (const GDomNode *pNode)
virtual	~GTransform ()

Static Public Member Functions
static void	restore_local_distances_pass (GMatrix &intrinsic, GNeighborGraph &ng, size_t neighborCount, GRand &rand)
	Perform a single pass over all the edges and attempt to restore local relationships. More...
static size_t	unfold_iter (GMatrix &intrinsic, GRand &rand, size_t neighborCount=12, double scaleFactor=1.01, size_t refinements=100)
	A convenience method for iteratively unfolding the manifold sampled by a matrix. (This method is not used within this class.) It finds the k-nearest neighbors within the matrix. (If the neighbor-graph is not connected, it doubles k until it is connected.) Next, this method multiplies the matrix by scaleFactor. Finally, it refines the points to restore local distances. (It would not typically be efficient to call this in a tight loop, because that would perform the neighbor-finding step each time.) Returns the number of neighbors actually used to find a connected graph. More...

Protected Attributes
size_t	m_neighborCount
size_t	m_passes
GRand	m_rand
size_t	m_refines_per_scale
double	m_scaleRate
size_t	m_targetDims

Additional Inherited Members
Protected Member Functions inherited from GClasses::GTransform
virtual GDomNode *	baseDomNode (GDom *pDoc, const char *szClassName) const
	Child classes should use this in their implementation of serialize. More...

Constructor & Destructor Documentation

GClasses::GScalingUnfolder::GScalingUnfolder

(

)

GClasses::GScalingUnfolder::GScalingUnfolder

(

GDomNode *

pNode

)

virtual GClasses::GScalingUnfolder::~GScalingUnfolder ( )

virtual

Member Function Documentation

GRand& GClasses::GScalingUnfolder::rand ( )

inline

Returns a reference to the pseudo-random number generator used by this object.

virtual GMatrix* GClasses::GScalingUnfolder::reduce ( const GMatrix &  in )

virtual

Reduces the dimensionality of "in".

Implements GClasses::GTransform.

static void GClasses::GScalingUnfolder::restore_local_distances_pass ( GMatrix &  intrinsic, GNeighborGraph &  ng, size_t  neighborCount, GRand &  rand  )

static

Perform a single pass over all the edges and attempt to restore local relationships.

void GClasses::GScalingUnfolder::setNeighborCount ( size_t  n )

inline

Specify the number of neighbors to use. (The default is 14.)

void GClasses::GScalingUnfolder::setPasses ( size_t  n )

inline

Specify the number of times to 'scale the data then recover local relationships'.

void GClasses::GScalingUnfolder::setRefinesPerScale ( size_t  n )

inline

Specify the number of times to refine the points after each scaling.

void GClasses::GScalingUnfolder::setScaleRate ( double  d )

inline

Specify the scaling rate. The default is 0.9.

void GClasses::GScalingUnfolder::setTargetDims ( size_t  n )

inline

Specify the number of dimensions in the output results.

void GClasses::GScalingUnfolder::unfold	(	GMatrix &	intrinsic,
		GNeighborGraph &	nf,
		size_t	encoderTrainIters = 0,
		GNeuralNetLearner *	pEncoder = NULL,
		GNeuralNetLearner *	pDecoder = NULL,
		const GMatrix *	pVisible = NULL
	)

Unfolds the points in intrinsic, such that distances specified in nf are preserved. If pVisible is non-NULL, then pEncoder will be incrementally trained to encode pVisible to intrinsic.

static size_t GClasses::GScalingUnfolder::unfold_iter ( GMatrix &  intrinsic, GRand &  rand, size_t  neighborCount = 12, double  scaleFactor = 1.01, size_t  refinements = 100  )

static

A convenience method for iteratively unfolding the manifold sampled by a matrix. (This method is not used within this class.) It finds the k-nearest neighbors within the matrix. (If the neighbor-graph is not connected, it doubles k until it is connected.) Next, this method multiplies the matrix by scaleFactor. Finally, it refines the points to restore local distances. (It would not typically be efficient to call this in a tight loop, because that would perform the neighbor-finding step each time.) Returns the number of neighbors actually used to find a connected graph.

Member Data Documentation

size_t GClasses::GScalingUnfolder::m_neighborCount

protected

size_t GClasses::GScalingUnfolder::m_passes

protected

GRand GClasses::GScalingUnfolder::m_rand

protected

size_t GClasses::GScalingUnfolder::m_refines_per_scale

protected

double GClasses::GScalingUnfolder::m_scaleRate

protected

size_t GClasses::GScalingUnfolder::m_targetDims

protected