Title :
Comments on approximating discrete probability distributions with dependence trees
fDate :
3/1/1989 12:00:00 AM
Abstract :
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.<>
Keywords :
Bayes methods; approximation theory; error statistics; minimisation; pattern recognition; probability; trees (mathematics); Bayes error rate; classification; discrete probability distributions; minimization; pattern recognition; probability distribution; product approximation; tree dependence approximation; Classification tree analysis; Entropy; Error analysis; Information systems; Information theory; Intelligent systems; Mutual information; Pattern recognition; Probability distribution; Upper bound;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on