| 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 |