# Gaussian Mixture Function

(Redirected from Gaussian mixture model)

A Gaussian Mixture Function is a mixture density function composed of two or more Gaussian density functions.

**Context:**- It can be a member of a Gaussian Mixture Model Family.
- It can range from being a Finite Gaussian Mixture Function (e.g. a 2-component Gaussian mixture) to being an Infinite Gaussian Mixture Function.
- It can range from being a Univariate Gaussian Mixture Function to being a Multivariate Gaussian Mixture Function.

**Example(s):****Counter-Example(s):****See:**Gaussian Process Neural Net, Gaussian Random Field, Finite Mixture Function, Vector Space.

## References

### 2010

- http://www.mathworks.com/matlabcentral/fileexchange/24867-gaussianmixturemodel-m/content/gaussian_mixture_model.m
- A Gaussian mixture model means that each data point is drawn (randomly) from one of C classes of data, with probability p_i of being drawn from class i, and each class is distributed as a Gaussian with mean standard deviation mu_i and sigma_i. Given a set of data drawn from such a distribution, we seek to estimate these unknown parameters.