Comments on Approximating Discrete Probability Distributions with Dependence Trees March 1989 (vol. 11 no. 3) pp. 333-335
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.21803
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. [1] P. M. Lewis, "Approximating probability distributions to reduce storage requirement,"Inform. and Contr., vol. 2, pp. 214-225, Sept. 1959.
Index Terms:
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)
Citation:
S.K.M. Wong, F.C.S. Poon, "Comments on Approximating Discrete Probability Distributions with Dependence Trees," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, no. 3, pp. 333-335, Mar. 1989, doi:10.1109/34.21803 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||