IJISA Vol. 9, No. 6, 8 Jun. 2017

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Computational Intelligence, Machine Learning, missing values, gaps' recovery, adaptive system, fuzzy clustering

An adaptive neural system which solves a problem of clustering data with missing values in an online mode with a permanent correction of restorable table elements and clusters’ centroids is proposed in this article. The introduced neural system is characterized by both a high speed and a simple numerical implementation. It can process information in a real-time mode.

Zhengbing Hu, Yevgeniy V. Bodyanskiy, Oleksii K. Tyshchenko, Vitalii M. Tkachov,"Fuzzy Clustering Data Arrays with Omitted Observations", International Journal of Intelligent Systems and Applications(IJISA), Vol.9, No.6, pp.24-32, 2017. DOI:10.5815/ijisa.2017.06.03

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