GClasses::GMixtureOfGaussians Class Reference

Detailed Description

This class uses Expectency Maximization to find the mixture of Gaussians that best approximates the data in a specified real attribute of a data set.

#include <GMixtureOfGaussians.h>

Public Member Functions
	GMixtureOfGaussians (int nKernelCount, GMatrix *pData, int nAttribute, double minVariance, GRand *pRand)
virtual	~GMixtureOfGaussians ()
double	iterate ()
	Returns the log likelihood of the current parameters. More...
void	params (int nKernel, double *pMean, double *pVariance, double *pWeight)
	Returns the current parameters of the specified kernel. More...

Static Public Member Functions
static GMixtureOfGaussians *	stochasticHammer (int nMinKernelCount, int nMaxKernelCount, int nItters, int nTrials, GMatrix *pData, int nAttribute, double minVariance, GRand *pRand)
	This tries to fit the data from several random starting points, and returns the best model it finds. More...
static void	test ()
	Performs unit tests for this class. Throws an exception if there is a failure. More...

Protected Member Functions
double	evalKernel (double x, int nKernel)
double	likelihoodOfEachCategoryGivenThisFeature (double x)

Protected Attributes
GNormalDistribution	m_dist
double	m_dMinVariance
int	m_nAttribute
int	m_nKernelCount
double *	m_pArrMeanVarWeight
double *	m_pCatLikelihoods
GMatrix *	m_pData
double *	m_pTemp

Constructor & Destructor Documentation

GClasses::GMixtureOfGaussians::GMixtureOfGaussians	(	int	nKernelCount,
		GMatrix *	pData,
		int	nAttribute,
		double	minVariance,
		GRand *	pRand
	)

virtual GClasses::GMixtureOfGaussians::~GMixtureOfGaussians ( )

virtual

Member Function Documentation

double GClasses::GMixtureOfGaussians::evalKernel ( double  x, int  nKernel  )

protected

double GClasses::GMixtureOfGaussians::iterate

(

)

Returns the log likelihood of the current parameters.

double GClasses::GMixtureOfGaussians::likelihoodOfEachCategoryGivenThisFeature ( double  x )

protected

void GClasses::GMixtureOfGaussians::params	(	int	nKernel,
		double *	pMean,
		double *	pVariance,
		double *	pWeight
	)

Returns the current parameters of the specified kernel.

static GMixtureOfGaussians* GClasses::GMixtureOfGaussians::stochasticHammer ( int  nMinKernelCount, int  nMaxKernelCount, int  nItters, int  nTrials, GMatrix *  pData, int  nAttribute, double  minVariance, GRand *  pRand  )

static

This tries to fit the data from several random starting points, and returns the best model it finds.

static void GClasses::GMixtureOfGaussians::test ( )

static

Performs unit tests for this class. Throws an exception if there is a failure.

Member Data Documentation

GNormalDistribution GClasses::GMixtureOfGaussians::m_dist

protected

double GClasses::GMixtureOfGaussians::m_dMinVariance

protected

int GClasses::GMixtureOfGaussians::m_nAttribute

protected

int GClasses::GMixtureOfGaussians::m_nKernelCount

protected

double* GClasses::GMixtureOfGaussians::m_pArrMeanVarWeight

protected

double* GClasses::GMixtureOfGaussians::m_pCatLikelihoods

protected

GMatrix* GClasses::GMixtureOfGaussians::m_pData

protected

double* GClasses::GMixtureOfGaussians::m_pTemp

protected