Advances and Applications in Statistics
Volume 4, Issue 3, Pages 357 - 377
(December 2004)
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ON THE OPTIMAL WEIGHTING OF HIGH-DIMENSIONAL BAYESIAN NETWORKS
Tatjana Pavlenko (Sweden) and Dietrich von Rosen (Sweden)
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Abstract: For
an augmented Bayesian network classifier we
propose a method of scoring a set of feature
nodes for the separation strength, wherein we
have combined a weighting technique and
growing dimension asymptotics in a single
framework. We show that the distribution of
the weighted classifier is asymptotically
Gaussian and establishes the weight-function
which is optimal in a sense of minimum
misclassification probability. |
Keywords and phrases: Bayesian network, augmenting, separation strength, growing dimension asymptotic, weighted classifier, limiting error probability. |
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