通过粗聚类处理相对接近性

22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003 Pub Date : 2003-07-24 DOI:10.1109/NAFIPS.2003.1226793

S. Hirano, S. Tsumoto

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引用次数: 0

摘要

提出了一种基于目标不可分辨性的聚类方法。即使对象的接近度被定义为相对接近度，它也为对象提供了良好的分区。这种方法的主要优点是它可以应用于不满足三角不等式的接近度量。此外，它可以与接近矩阵一起使用，因此不需要直接访问原始数据值。

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Dealing with relatively proximity by rough clustering

This paper presents a new clustering method based on the indiscernibility of objects. It provides good partition to objects even when the proximity of objects is defined as relative proximity. The main benefit of this method is that it can be applied to proximity measures that do not satisfy the triangular inequality. Additionally, it may be used with a proximity matrix-thus it does not require direct access to the original data values.

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22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003

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