Kernel Functions Derived from Fuzzy Clustering and Their Application to Kernel Fuzzyc-Means
2011 ◽
Vol 15
(1)
◽
pp. 90-94
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Keyword(s):
Among widely used kernel functions, such as support vector machines, in data analysis, the Gaussian kernel is most often used. This kernel arises in entropy-based fuzzyc-means clustering. There is reason, however, to check whether other types of functions used in fuzzyc-means are also kernels. Using completely monotone functions, we show they can be kernels if a regularization constant proposed by Ichihashi is introduced. We also show how these kernel functions are applied to kernel-based fuzzyc-means clustering, which outperform the Gaussian kernel in a typical example.
2005 ◽
Vol 6B
(10)
◽
pp. 961-973
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2011 ◽
pp. 93-122
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2010 ◽
pp. 106-112
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Keyword(s):
2003 ◽
Vol 15
(7)
◽
pp. 1667-1689
◽
Keyword(s):
2014 ◽
Vol 511-512
◽
pp. 467-474
Keyword(s):
2014 ◽
Vol 644-650
◽
pp. 4314-4318