一种新的基于模糊接近矩阵的模糊聚类有效性指标

2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence Pub Date : 2013-09-08 DOI:10.1109/BRICS-CCI-CBIC.2013.87

Rafael Xavier Valente, Antonio Braga, W. Pedrycz

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引用次数: 2

摘要

针对模糊c均值算法生成的模糊分区，提出了一种新的有效性指标。提出的有效性指标是基于模糊聚类划分算法(如FCM)生成的隶属度矩阵产生的接近矩阵计算因子。实验结果表明，该方法与其他已知的度量方法一致，并且与接近矩阵的数据集结构一致。

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A New Fuzzy Clustering Validity Index Based on Fuzzy Proximity Matrices

This paper presents a new validity index for fuzzy partitions generated by the fuzzy c-means algorithm. The proposed validity index is based on the calculation of factors from the proximity matrix generated from the membership matrix generated by a fuzzy clustering partition algorithm, such as FCM. The experimental results show that the proposed approach is consistent with other well-known metrics and with the dataset structure as observed from Proximity Matrices.

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2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence

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