Gaussian Mixture Function
(Redirected from Gaussian mixture model)
- 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.
- See: Gaussian Process Neural Net, Gaussian Random Field, Finite Mixture Function, Vector Space.
- 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.