DocumentCode :
1748816
Title :
BYY binary independent systems, unsupervised harmony learning, and data mining of production rules
Author :
Xu, Lei
Author_Institution :
Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, China
Volume :
3
fYear :
2001
fDate :
2001
Firstpage :
1920
Abstract :
A concise systematic view on the Bayesian Ying-Yang (BYY) modular binary independent system is provided. The details on three typical architectures are discussed for both parameter learning and model selection, under the names of local binary factorial learning, local LMESR learning and competitive binary ICA learning, respectively. Then, they are applied to unsupervised knowledge mining via production rules with model selection that decides an appropriate number of rules, such that the redundancy and conflict among the rules can be reduced
Keywords :
Bayes methods; data mining; unsupervised learning; Bayesian Ying-Yang modular binary independent system; competitive binary ICA learning; data mining; local LMESR learning; local binary factorial learning; model selection; parameter learning; production rules; unsupervised harmony learning; unsupervised knowledge mining; Computer science; Data engineering; Data mining; Hidden Markov models; Independent component analysis; Principal component analysis; Production systems; Source separation; Supervised learning; Unsupervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
ISSN :
1098-7576
Print_ISBN :
0-7803-7044-9
Type :
conf
DOI :
10.1109/IJCNN.2001.938457
Filename :
938457
Link To Document :
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