Abstract
Based on the fuzzy c-means clustering method maximized with the Tsallis entropy, we have achieved its extension that assigns the q parameter of Tsallis entropy to each cluster as \(q_i\).
In this method, however, there remains three problems. That is, (1) determination \(q_i\) according to the data distribution, (2) occurrence of abnormal bias of \(q_i\), and (3) calculation termination condition of \(q_i\). In this article, we propose a new calculation method and a termination condition of \(q_i\), and show its effects by experiments.
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Yasuda, M. (2020). Determination of Multiple q Values for Tsallis-Entropy-Maximized-FCM. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1074. Springer, Cham. https://doi.org/10.1007/978-3-030-32456-8_83
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DOI: https://doi.org/10.1007/978-3-030-32456-8_83
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