Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning
This paper proposes a topological clustering algorithm by integrating topological structure and information theoretic learning, i.e., correntropy, into adaptive resonance theory (ART). Specifically, the proposed algorithm utilizes the correntropy induced metric (CIM) for defining a similarity measur...
Main Authors: | Masuyama, Naoki, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki, Nojima, Yusuke, Liu, Yiping |
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Format: | Article |
Published: |
Institute of Electrical and Electronics Engineers
2019
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Subjects: |
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