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<p>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.</p>
pattern recognition; classification; discrete probability distributions; probability distribution; product approximation; tree dependence approximation; Bayes error rate; minimization; approximation theory; Bayes methods; error statistics; minimisation; pattern recognition; probability; trees (mathematics)
F.C.S. Poon, S.K.M. Wong, "Comments on Approximating Discrete Probability Distributions with Dependence Trees", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 11, no. , pp. 333-335, March 1989, doi:10.1109/34.21803
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