mlpack::gmm(3) | MLPACK | mlpack::gmm(3) |
NAME¶
mlpack::gmm - Gaussian Mixture Models.SYNOPSIS¶
Classes¶
class DiagonalConstraint
Functions¶
double phi (const double x, const double mean, const double var)
Detailed Description¶
Gaussian Mixture Models.Function Documentation¶
double mlpack::gmm::phi (const doublex, const doublemean, const doublevar) [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.
Author¶
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