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FCMand

于 2020-11-23 发布

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下载积分: 1 下载次数: 3

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说明：在聚类分析中,模糊c-均值算法是应用最广泛的聚类算法之一,针对该算法对初始化敏感,容易陷入局部极小点的缺点,论文提出了一种基于核的模糊聚类算法.在算法中将核方法与模糊可能性算法相结合,将模糊c-均值算法结果作为初始中心,放松了对隶属度归一化的条件,对噪声有更好的处理能力.IRIS数据和人造数据的实验结果表明该算法的有效性(Chun-Fu Lin,Sheng-De Wang.Fuzzy support vector machines.[J].IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council,2002,13(2).464-71.)

文件列表：

FCMand\data.mat, 5128 , 2020-11-03
FCMand\FCMClust.m, 5232 , 2009-06-28
FCMand\gauss_Kernel.m, 529 , 2020-11-04
FCMand\kernelFun\gauss_Kernel.m, 529 , 2020-11-04
FCMand\kfcm.m, 868 , 2020-11-04
FCMand\KFCMClust.m, 6993 , 2020-11-04
FCMand\twoCircles.mat, 5093 , 2016-12-09
FCMand\核聚类算法.pdf, 128731 , 2005-05-06
FCMand\kernelFun, 0 , 2020-11-04
FCMand, 0 , 2020-11-18

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