Parameter learning in MTE networks using incomplete data
Bayesian networks with mixtures of truncated exponentials (MTEs) are gaining popularity as a flexible modelling framework for hybrid domains. MTEs support efficient and exact inference algorithms, but estimating an MTE from data has turned out to be a difficult task. Current methods suffer from a co...
| Main Authors: | , , , |
|---|---|
| Format: | info:eu-repo/semantics/report |
| Language: | English |
| Published: |
2012
|
| Online Access: | http://hdl.handle.net/10835/1546 |