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Alternative Noise Clustering Algorithm

机译:替代噪声聚类算法

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摘要

Based on a new distance, a novel noise-resistant fuzzy clustering algorithm called alternative noise clustering (ANC) algorithm is proposed, ANC is an extension of the noise clustering (NC) algorithm proposed by Dave. By replacing the Euclidean distance used in the objective function of NC algorithm, a new distance (non-Euclidean distance) is introduced in NC algorithm. Based on robust statistical point of view and influence function, the non-Euclidean distance is more robust than the Euclidean distance. So the ANC algorithm is more robust than the NC algorithm. Moreover, with the new distance ANC can deal with noises or outliers better than NC and fuzzy c-means (FCM). Performing experiments on data sets shows the better performance of the proposed algorithm.
机译:在新距离的基础上,提出了一种新的抗噪声模糊聚类算法,称为替代噪声聚类(ANC)算法,它是Dave提出的噪声聚类(NC)算法的扩展。通过替换用于NC算法目标函数的欧几里得距离,在NC算法中引入了新的距离(非欧几里得距离)。基于鲁棒的统计观点和影响函数,非欧几里得距离比欧几里得距离更鲁棒。因此,ANC算法比NC算法更健壮。此外,有了新的距离,ANC可以比NC和模糊c均值(FCM)更好地处理噪声或离群值。对数据集进行实验表明该算法具有更好的性能。

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