# mdninit

## Purpose

Initialise the weights in a Mixture Density Network.

## Synopsis

    net = mdninit(net, prior)
    net = mdninit(net, prior, t, options)

## Description

`net = mdninit(net, prior)` takes a Mixture Density Network `net` and sets the weights and biases by sampling from a Gaussian distribution. It calls `mlpinit` for the MLP component of `net`.

`net = mdninit(net, prior, t, options)` uses the target data `t` to initialise the biases for the output units after initialising the other weights as above. It calls `gmminit`, with `t` and `options` as arguments, to obtain a model of the unconditional density of `t`. The biases are then set so that `net` will output the values in the Gaussian mixture model.

## See Also

`mdn`, `mlp`, `mlpinit`, `gmminit`

Pages: Index

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

David J Evans (1998)