mlpack::gmm Namespace Reference

Gaussian Mixture Models. More...

Classes
class	EMFit
	This class contains methods which can fit a GMM to observations using the EM algorithm. More...
class	GMM
	A Gaussian Mixture Model (GMM). More...
Functions
double	phi (const double x, const double mean, const double var)
	Calculates the univariate Gaussian probability density function.
double	phi (const arma::vec &x, const arma::vec &mean, const arma::mat &cov)
	Calculates the multivariate Gaussian probability density function.
double	phi (const arma::vec &x, const arma::vec &mean, const arma::mat &cov, const std::vector< arma::mat > &d_cov, arma::vec &g_mean, arma::vec &g_cov)
	Calculates the multivariate Gaussian probability density function and also the gradients with respect to the mean and the variance.
void	phi (const arma::mat &x, const arma::vec &mean, const arma::mat &cov, arma::vec &probabilities)
	Calculates the multivariate Gaussian probability density function for each data point (column) in the given matrix, with respect to the given mean and variance.

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Detailed Description

Gaussian Mixture Models.

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Function Documentation

double mlpack::gmm::phi	(	const double	x,
		const double	mean,
		const double	var
	)		[inline]

Calculates the univariate Gaussian probability density function.

Example use:

 double x, mean, var;
 ....
 double f = phi(x, mean, var);

Parameters:

x	Observation.
mean	Mean of univariate Gaussian.
var	Variance of univariate Gaussian.

Returns:

Probability of x being observed from the given univariate Gaussian.

Definition at line 46 of file phi.hpp.

References M_PI.

Referenced by mlpack::distribution::GaussianDistribution::Probability().

double mlpack::gmm::phi	(	const arma::vec &	x,
		const arma::vec &	mean,
		const arma::mat &	cov
	)		[inline]

Calculates the multivariate Gaussian probability density function.

Example use:

 extern arma::vec x, mean;
 extern arma::mat cov;
 ....
 double f = phi(x, mean, cov);

Parameters:

x	Observation.
mean	Mean of multivariate Gaussian.
cov	Covariance of multivariate Gaussian.

Returns:

Probability of x being observed from the given multivariate Gaussian.

Definition at line 68 of file phi.hpp.

References M_PI.

double mlpack::gmm::phi	(	const arma::vec &	x,
		const arma::vec &	mean,
		const arma::mat &	cov,
		const std::vector< arma::mat > &	d_cov,
		arma::vec &	g_mean,
		arma::vec &	g_cov
	)		[inline]

Calculates the multivariate Gaussian probability density function and also the gradients with respect to the mean and the variance.

Example use:

 extern arma::vec x, mean, g_mean, g_cov;
 std::vector<arma::mat> d_cov; // the dSigma
 ....
 double f = phi(x, mean, cov, d_cov, &g_mean, &g_cov);

Definition at line 94 of file phi.hpp.

References M_PI.

void mlpack::gmm::phi	(	const arma::mat &	x,
		const arma::vec &	mean,
		const arma::mat &	cov,
		arma::vec &	probabilities
	)		[inline]

Calculates the multivariate Gaussian probability density function for each data point (column) in the given matrix, with respect to the given mean and variance.

Parameters:

x	List of observations.
mean	Mean of multivariate Gaussian.
cov	Covariance of multivariate Gaussian.
probabilities	Output probabilities for each input observation.

Definition at line 138 of file phi.hpp.

References M_PI.