Fuzzy Clustering Data Given on the Ordinal Scale Based on Membership and Likelihood Functions Sharing
Автор: Zhengbing Hu, Yevgeniy V. Bodyanskiy, Oleksii K. Tyshchenko, Viktoriia O. Samitova
Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa
Статья в выпуске: 2, 2017 года.
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A task of clustering data given on the ordinal scale under conditions of overlapping clusters has been considered. It's proposed to use an approach based on membership and likelihood functions sharing. A number of performed experiments proved effectiveness of the proposed method. The proposed method is characterized by robustness to outliers due to a way of ordering values while constructing membership functions.
Computational Intelligence, Machine Learning, ordinal data, FCM, membership function, likelihood function
Короткий адрес: https://sciup.org/15010079
IDR: 15010079
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