# gmminit

## Purpose

Initialises Gaussian mixture model from data

## Synopsis

    mix = gmminit(mix, x, options)

## Description

`mix = gmminit(mix, x, options)` uses a dataset `x` to initialise the parameters of a Gaussian mixture model defined by the data structure `mix`. The k-means algorithm is used to determine the centres. The priors are computed from the proportion of examples belonging to each cluster. The covariance matrices are calculated as the sample covariance of the points associated with (i.e. closest to) the corresponding centres. For a mixture of PPCA model, the PPCA decomposition is calculated for the points closest to a given centre. This initialisation can be used as the starting point for training the model using the EM algorithm.

## Example

    mix = gmm(3, 2);
    options = foptions;
    options(14) = 5;
    mix = gmminit(mix, data, options);

This code sets up a Gaussian mixture model with 3 centres in 2 dimensions, and then initialises the parameters from the data set `data` with 5 iterations of the k means algorithm.

## See Also

`gmm`

Pages: Index

Copyright (c) Ian T Nabney (1996-9)