具有容差数据的熵正则化模糊c线

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI:10.1109/FUZZY.2009.5277176

Y. Kanzawa, Y. Endo, S. Miyamoto

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摘要

本文提出了一种新的基于熵正则化模糊c线的聚类算法，该算法可以处理具有一定误差的数据。首先，将公差的概念引入到聚类优化问题中。接下来，用Karush-Kuhn-Tucker条件求解问题。最后，根据问题的求解结果构造算法。给出了该方法的一些数值算例。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Entropy regularized fuzzy C-lines for data with tolerance

This paper presents a new clustering algorithm, which is based on entropy regularized fuzzy c-lines, can treat data with some errors. First, the tolerance is formulated and introduce into optimization problem of clustering. Next, the problem is solved using Karush-Kuhn-Tucker conditions. Last, the algorithm is constructed based on the results of solving the problem. Some numerical examples for the proposed method are shown.

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2009 IEEE International Conference on Fuzzy Systems

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