Peter Antal, Geert Fannes, Dirk Timmerman, Yves Moreau, Bart De Moor  Home/Search
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Abstract: Incorporating prior knowledge into black-box classifiers is still much of an open problem. We propose a hybrid Bayesian methodology that consists in encoding prior knowledge in the form of a (Bayesian) belief network and then using this knowledge to estimate an informative prior for a blackbox model (e.g. a multilayer perceptron). Two technical approaches are proposed for the transformation of the belief network into an informative prior. The first one consists in generating samples according... (Update)
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BibTeX entry: (Update)
Antal P, Fannes G, Timmerman D, De Moor B, Moreau Y. Bayesian applications of belief networks and multilayer perceptrons for ovarian tumor 24 classification with rejection, Artif Intell Med 2003, in press. http://citeseer.ist.psu.edu/antal03bayesian.html More
@misc{ antal03bayesian,
author = "P. Antal and G. Fannes and D. Timmerman and B. De Moor and Y. Moreau",
title = "Bayesian applications of belief networks and multilayer perceptrons for
ovarian tumor 24 classification with rejection",
text = "Antal P, Fannes G, Timmerman D, De Moor B, Moreau Y. Bayesian applications
of belief networks and multilayer perceptrons for ovarian tumor 24 classification
with rejection, Artif Intell Med 2003, in press.",
year = "2003",
url = "citeseer.ist.psu.edu/antal03bayesian.html" }
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