Multiple kernel for clustering
2016-08-23
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In this paper, kernel interval type-2 fuzzy c-means
clustering (KIT2FCM) and multiple kernel interval type 2 fuzzy
c-means clustering (MKIT2FCM) are proposed for clustering
problems. Besides, KIT2FCM algorithm was built on the basis of
the kernel learning method and the interval type 2 fuzzy set to
overcome some drawbacks of the conventional FCM. While the
interval type 2 fuzzy set has advantages of handling uncertainty
in clustering, the kernel method suggests the possibility of finding
clusters with various shapes. In this paper, we also introduces a
clustering (KIT2FCM) and multiple kernel interval type 2 fuzzy
c-means clustering (MKIT2FCM) are proposed for clustering
problems. Besides, KIT2FCM algorithm was built on the basis of
the kernel learning method and the interval type 2 fuzzy set to
overcome some drawbacks of the conventional FCM. While the
interval type 2 fuzzy set has advantages of handling uncertainty
in clustering, the kernel method suggests the possibility of finding
clusters with various shapes. In this paper, we also introduces a
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