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...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Published: |
Institute of Electrical and Electronics Engineers
2019
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/24041/ https://doi.org/10.1109/ACCESS.2019.2921832 |
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