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Parameter Learning for Bayesian Networks with Strict Qualitative Influences
by
Ad Feelders
,
Robert Van Straalen
BibTeX
@MISC{Feelders_parameterlearning,
author = {Ad Feelders and Robert Van Straalen},
title = {Parameter Learning for Bayesian Networks with Strict Qualitative Influences},
year = {}
}
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Abstract
Abstract. We propose a new method for learning the parameters of a Bayesian network with qualitative influences. The proposed method aims to remove unwanted (context-specific) independencies that are created by the order-constrained maximum likelihood (OCML) estimator. This is achieved by averaging the OCML estimator with the fitted probabilities of a first-order logistic regression model. We show experimentally that the new learning algorithm does not perform worse than OCML, and resolves a large part of the independencies. 1
