Bayesian Network with Association Rules Applied in the Recognition of Handwritten Digits

Abstract:

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Classification Based on Association (CBA) algorithm built a classifier based on the association rules, but without considering the uncertainty in the classification problem. This paper proposed a Bayesian network classifier based on the association rules. The algorithm extracts the candidate set uses association rules and classification algorithms related to the network, then uses “greedy hill-climbing algorithm” to learn network structure to get a better topology, and verify that this algorithm is valid on handwritten numeral recognition.

Info:

Periodical:

Edited by:

Yanwen Wu

Pages:

7-12

DOI:

10.4028/www.scientific.net/AMR.187.7

Citation:

W. Q. Zhao et al., "Bayesian Network with Association Rules Applied in the Recognition of Handwritten Digits", Advanced Materials Research, Vol. 187, pp. 7-12, 2011

Online since:

February 2011

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Price:

$35.00

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