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