Data mining, unsupervised learning and Bayesian Ying-Yang theory
Refereed conference paper presented and published in conference proceedings


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AbstractA number of unsupervised learning methods or algorithms have been summarized from the perspective of their potential uses in data mining (DM). Then, major unsupervised learning tasks are systematically viewed under a unified framework called Bayesian Ying-Yang learning. Furthermore, it is shown systematically how 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.
All Author(s) ListXu Lei
Name of ConferenceInternational Joint Conference on Neural Networks (IJCNN'99)
Start Date of Conference10/07/1999
End Date of Conference16/07/1999
Place of ConferenceWashington, DC, USA
Country/Region of ConferenceUnited States of America
Detailed descriptionvol.4 of 6
Year1999
Month12
Day1
Volume Number4
Pages2520 - 2525
LanguagesEnglish-United Kingdom

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