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

香港中文大學研究人員

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摘要A 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.
著者Xu Lei
會議名稱International Joint Conference on Neural Networks (IJCNN'99)
會議開始日10.07.1999
會議完結日16.07.1999
會議地點Washington, DC, USA
會議國家/地區美國
詳細描述vol.4 of 6
出版年份1999
月份12
日期1
卷號4
頁次2520 - 2525
語言英式英語

上次更新時間 2021-24-03 於 14:45