Two classes of algorithms for data clustering

Authors:
Sadaaki Miyamoto
Affiliations:
Department of Risk Engineering, Faculty of Systems and Information Engineering, University of Tsukuba, Tsukuba, Ibaraki, Japan
Venue:
IUKM'11 Proceedings of the 2011 international conference on Integrated uncertainty in knowledge modelling and decision making
Year:
2011

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Abstract

The two classes of agglomerative hierarchical clustering algorithms and K-means algorithms are overviewed. Moreover recent topics of kernel functions and semi-supervised clustering in the two classes are discussed. This paper reviews traditional methods as well as new techniques.