gtm

Purpose

Synopsis

net = gtm(dimlatent, nlatent, dimdata, ncentres, rbfunc)
net = gtm(dimlatent, nlatent, dimdata, ncentres, rbfunc, prior)

Description

net = gtm(dimlatent, nlatent, dimdata, ncentres, rbfunc), takes the dimension of the latent space dimlatent, the number of data points sampled in the latent space nlatent, the dimension of the data space dimdata, the number of centres in the RBF model ncentres, the activation function for the RBF rbfunc and returns a data structure net. The parameters in the RBF and GMM sub-models are set by calls to the corresponding creation routines rbf and gmm.

The fields in net are

  type = 'gtm'
  nin = dimension of data space
  dimlatent = dimension of latent space
  rbfnet = RBF network data structure
  gmmnet = GMM data structure
  X = sample of latent points

net = gtm(dimlatent, nlatent, dimdata, ncentres, rbfunc, prior), sets a Gaussian zero mean prior on the parameters of the RBF model. prior must be a scalar and represents the inverse variance of the prior distribution. This gives rise to a weight decay term in the error function.

See Also

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