A Research on Mixture Splitting for CHMM Based on DBC
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| Title | A Research on Mixture Splitting for CHMM Based on DBC |
| Authors | |
| Abstract | EM (expectation-maximization) algorithm is a classical method for parameter estimation of HMM (Hidden Markov model). Concerning that EM algorithm is easily affected by initial parameter values, a mixture splitting algorithm based on decision boundary confusion(DBC) was proposed to describe more about boundary distribution. The algorithm mainly includes four aspects: firstly the number of incremented mixtures for every decision boundary could be determined according to decision boundary confusion; secondly the mixtures which are the closest to the decision boundary are chosen to split; thirdly the split mean of mixture is in the direction of decision boundary; finally the mixture number of a state is determined by the confusion between states. Our experiments show that our proposed algorithm is more effective for classification using HMM. |
| Publisher | ACADEMY PUBLISHER |
| Date | 2009-11-01 |
| Source | Journal of Computers Vol 4, No 11 (2009): Special Issue: Selected Best Papers of WKDD 2008 - Track on Information Proces |
| Rights | Copyright © ACADEMY PUBLISHER - All Rights Reserved.To request permission, please check out URL: http://www.academypublisher.com/copyrightpermission.html. |