This classifier demonstrates superior accuracy to other state-of-the-art Bayesian network and multinet classifiers on 32 real-world databases. Keywords.
Abstract. A Bayesian multinet classifier allows a different set of independence assertions among variables in each of a set of local Bayesian networks ...
Aug 17, 2006 · This classifier demonstrates superior accuracy to other state-of-the-art Bayesian network and multinet classifiers on 32 real-world databases.
We describe an adaptive algorithm for improving the performance of Bayesian Network Classifi ers (BNCs) in an on-line learning framework. Instead of choosing a ...
This classifier demonstrates superior accuracy to other state-of-the-art Bayesian network and multinet classifiers on 32 real-world databases. Original language ...
Bibliographic details on Bayesian Class-Matched Multinet Classifier.
A Bayesian multinet classifier allows a different set of independence assertions among variables in each of a set of local Bayesian networks.
We introduce a method for chaining binary Bayesian classifiers that combines the strengths of classi- fier chains and Bayesian networks for multidimen- sional ...
Missing: Matched Multinet
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In this paper, a class of models called dynamic Bayesian multinets and a method to induce their structure for the classification task is described. In this ...
Jan 11, 2015 · The first disadvantage is that the Naive Bayes classifier makes a very strong assumption on the shape of your data distribution, i.e. any two ...