Allan,
in the following paper we describe learning the
structure of a Bayesian Network from a dataset
with nonlinear relationships between continuous
variables. The Bayesian Network uses kernel-based
estimators to model those nonlinear relationships:
"Discovering Structure in Continuous Variables using
Bayesian Networks"
Reimar Hofmann and Volker Tresp
NIPS*95
(http://wwwbrauer.informatik.tu-muenchen.de/~hofmannr/nips95_abstr.html)
In a second paper we describe structure learning in
Markov Networks for nonlinear relationships
between continuous variables:
"Nonlinear Markov Networks for Continuous Variables"
Reimar Hofmann and Volker Tresp
NIPS*97
(http://wwwbrauer.informatik.tu-muenchen.de/~hofmannr/nips97_abstr.html)
Best regards,
Reimar
--
___________________________________________________________________________
Reimar Hofmann
ZT IK 4 www:
http://www7.informatik.tu-muenchen.de/~hofmannr
Siemens AG, CR & D Email: [EMAIL PROTECTED]
81730 Muenchen Tel: +49/89/636-50804
Germany Fax: +49/89/636-49767