DocumentCode :
3261411
Title :
Classification and Clustering: A Perspective toward Risk Mining
Author :
Miyamoto, Sadaaki
Author_Institution :
Dept. of Risk Eng., Tsukuba Univ., Ibaraki
fYear :
2006
fDate :
Dec. 2006
Firstpage :
726
Lastpage :
730
Abstract :
In this paper three topics concerning data clustering are discussed. One is an association found in supervised classification and clustering, whereby new techniques of clustering can be developed some of which are described here. Next two are concerned with risk mining. The consideration of associations between the above two classes of methods is related to the second topic in which clustering in the presence of rough sets is considered. The third is related to mining actual data on a risk issue, where the method of fuzzy clustering is applied. Throughout these considerations, we focus more on a research perspective, i.e., possibilities in near future rather than an established method or algorithm
Keywords :
data mining; fuzzy set theory; learning (artificial intelligence); regression analysis; risk analysis; rough set theory; data clustering; fuzzy clustering; research perspective; risk mining; rough sets; supervised classification; supervised clustering; Clustering algorithms; Data engineering; Data mining; Fuzzy sets; Logic; Nearest neighbor searches; Predictive models; Risk analysis; Rough sets; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2702-7
Type :
conf
DOI :
10.1109/ICDMW.2006.41
Filename :
4063721
Link To Document :
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