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Weighting Exponent Selection of Fuzzy C-Means via Jacobian Matrix

机译:通过Jacobian矩阵加权模糊C-Clane的指数选择

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FCM is a popular clustering algorithm and applied in various areas. However, there are still some problems to be solved including the selection of weighting exponent m and convergence analysis. In this paper, we present an efficient method to identify the proper range of m and convergence rate by a new Jacobian matrix of FCM. A series of experimental results on both synthetical data and real-world data validate the proposed theoretical results.
机译:FCM是一种流行的聚类算法,应用于各种区域。然而,仍然存在一些问题,包括选择加权指数M和收敛分析。在本文中,我们提出了一种有效的方法来识别FCM的新Jacobian矩阵的适当范围的M和收敛速率。综合数据和现实世界数据的一系列实验结果验证了提出的理论结果。

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