net = mdninit(net, prior) net = mdninit(net, prior, t, options)
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.
mdn, mlp, mlpinit, gmminitCopyright (c) Ian T Nabney (1996-9)
David J Evans (1998)