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://readera.ru/15010079

IDR: 15010079

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