可能性c回归模型聚类算法

C. Kung, Hong-Chi Ku, J. Su
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引用次数: 6

摘要

本文将可能性c均值(PCM)聚类算法应用于模糊c回归模型(FCRM)聚类算法,提出了一种新的聚类算法——可能性c回归模型(PCRM)聚类算法。PCRM聚类算法放宽了每个聚类的列和约束结果,有效地缓解了噪声数据。最后,通过仿真实例验证了PCRM聚类算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Possibilistic c-regression models clustering algorithm
The purpose of this paper is to apply the possibilistic c-means (PCM) clustering algorithm to the fuzzy c-regression models (FCRM) clustering algorithm and propose a new clustering algorithm named possibilistic c-regression models (PCRM). The PCRM clustering algorithms relaxes the column sum constrain result in each cluster, it will alleviate the noisy data effectively. Finally, the simulation examples are provided to demonstrate the effectiveness of the PCRM clustering algorithm.
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