Comments on approximating discrete probability distributions with dependence trees

C.K. Chow and C.N. Liu (1968) introduced the notion of three dependence to approximate a kth-order probability distribution. More recently, A.K.C. Wong and C.C. Wang (1977) proposed a different product approximation. The present authors show that the tree dependence approximation suggested by Chow a...

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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 1989-03, Vol.11 (3), p.333-335
Main Authors: Wong, S.K.M., Poon, F.C.S.
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Classification tree analysis
Computer science
control theory
systems
Entropy
Error analysis
Exact sciences and technology
Information systems
Information theory
Intelligent systems
Learning and adaptive systems
Mutual information
Pattern recognition
Probability distribution
Upper bound
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Summary:C.K. Chow and C.N. Liu (1968) introduced the notion of three dependence to approximate a kth-order probability distribution. More recently, A.K.C. Wong and C.C. Wang (1977) proposed a different product approximation. The present authors show that the tree dependence approximation suggested by Chow and Liu can be derived by minimizing an upper bound of the Bayes error rate under certain assumptions. They also show that the method proposed by Wong and Wang does not necessarily lead to fewer misclassifications, because it is a special case of such a minimization procedure.< >
ISSN:0162-8828
1939-3539
2160-9292
DOI:10.1109/34.21803