# gtm

## Purpose

Create a Generative Topographic Map.

## 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

`gtmfwd`, `gtmpost`, `rbf`, `gmm`

Pages: Index

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