@article{Varando2015c,

title = {Decision boundary for discrete Bayesian network classifiers},

author = {Gherardo Varando and Concha Bielza and Pedro Larra\~{n}aga},

url = {http://cig.fi.upm.es/node/881 http://cig.fi.upm.es/articles/2015/Varando-2015-JMLR.pdf},

year  = {2015},

date = {2015-01-01},

journal = {Journal of Machine Learning Research},

abstract = {Bayesian network classi ers are a powerful machine learning tool. In order to evaluate the expressive power of these models, we compute families of polynomials that sign-represent decision functions induced by Bayesian network classi ers. We prove that those families are linear combinations of products of Lagrange basis polynomials. In absence of V -structures in the predictor sub-graph, we are also able to prove that this family of polynomials does indeed characterize the speci c classi er considered. We then use this representation to bound the number of decision functions representable by Bayesian network classi ers with a given structure},

keywords = {Bayesian networks, CASI CAM CM, CIG UPM, decision boundary, Journal, Lagrange basis, polynomial, supervised classication, threshold function},

pubstate = {published},

tppubtype = {article}

}