PRTools contents |
GTM
expectation-maximisation algorithm.
[W,L] = GTM (A,K,M,MAPTYPE,REG,EPS,MAXITER)
Input | |
A | Dataset or double matrix |
K | Vector containing number of nodes per dimension (default: [5 5], 2D map) |
M | Vector containing number of basis functions per dimension (default: [10 10]) |
MAPTYPE | Map onto mean of posterior ('mean', default) or mode ('mode') |
REG | Regularisation (default: 0) |
EPS | Change in likelihood to stop training (default: 1e-5) |
MAXITER | Maximum number of iterations (default: inf) |
Output | |
W | GTM mapping |
L | Likelihood |
Trains a Generative Topographic Mapping of any dimension, using the EM algorithm.
Bishop, C.M., Svensen, M. and Williams, C.K.I., "GTM: The Generative Topographic Mapping", Neural Computation 10(1):215-234, 1998.
PRTools contents |