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Wong and Poon [1] showed that Chow and Liu’s tree dependence approximation can be derived by minimizing an upper bound of the Bayes error rate. Wong and Poon’s result was obtained by expanding the conditional entropy H(w|X). We derive the correct expansion of H(w|X) and present its implication.
bayes error rate, entropy, mutual information, classification, dependence tree approximation

V. V. Phoha and K. S. Balagani, "On the Relationship Between Dependence Tree Classification Error and Bayes Error Rate," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 29, no. , pp. 1866-1868, 2007.
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