DocumentCode
1854900
Title
Data mining, unsupervised learning and Bayesian ying-yang theory
Author
Xu, Lei
Author_Institution
Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong
Volume
4
fYear
1999
fDate
1999
Firstpage
2520
Abstract
A number of unsupervised learning methods or algorithms have been summarized from the perspective of their potential uses in data mining. Major unsupervised learning tasks are then systematically viewed under a unified framework called Bayesian ying-yang (BYY) learning. Furthermore, it is shown systematically how the BYY learning theory can guide us not only to revisit the existing major unsupervised learning methods and results, but also to obtain a number of new methods and results
Keywords
Bayes methods; data mining; neural nets; principal component analysis; unsupervised learning; Bayesian ying-yang learning; data mining; knowledge discovery; machine learning; principal component analysis; unsupervised learning; Bayesian methods; Clustering algorithms; Curve fitting; Data mining; Data visualization; Delta modulation; Neural networks; Principal component analysis; Surface fitting; Unsupervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-5529-6
Type
conf
DOI
10.1109/IJCNN.1999.833469
Filename
833469
Link To Document