# Mixture model

# 1d infinite gaussian mixture model in matlab

# 2d infinite gaussian mixture model in matlab

# Gaussian mixture model in matlab

# Bayesian robust state space mixture model in matlab

# Bayesian robust mixture model in matlab

# Bayesian robust regression mixture model in matlab

# Em Algorithm Matlab Code

# Gaussian mixture model in matlab

# Bayesian robust simplicial mixture model in matlab

# Gmm Matlab Code

Generalized method of moments (GMM) is a generic method for estimating parameters in statistical models. Usually it is applied in the context of semiparametric models, where the parameter of interest is finite-dimensional, whereas the full shape of the distribution function of the data may not be known, and therefore the maximum likelihood estimation is not applicable.

# Expectation maximization of gaussian mixture models via cuda in matlab

# 3d visualization of gmm learning via the em algorithm in matlab

# Gaussian mixture model (gmm) gaussian mixture regression (gmr) in matlab

# Expectation maximization algorithm with gaussian mixture model in matlab

# Gaussian mixture modeling gui (gmm demo) in matlab

# Useful matlab functions for speaker recognition using adapted gaussian mixture model

# Gaussian mixture model in matlab

# Em algorithm for gaussian mixture model with background noise in matlab

# Ziheng gmm in matlab

# Community detection use gaussian mixture model in matlab

# Parameter estimation technique for general datasets in matlab

# K Means Clustering Matlab Code

k-means clustering is a method of vector quantization, originally from signal processing, that is popular for cluster analysis in data mining. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells.