Clustering uncertain interval data using a new Hausdorff-based metric

M. Zarandi, M. Avazbeigi, M. Anssari, I. Turksen
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Abstract

This paper presents a new index for measuring interval distances and its related metric. The proposed index and metric are both based on the Hausdorff distance which can be used for clustering uncertain interval data. Then using the new metric, a clustering method is introduced for clustering of intervals. Finally, some experiments are provided to validate the method. Results show that the method can identify appropriate clusters efficiently.
使用新的基于hausdorff的度量聚类不确定区间数据
本文提出了一种测量区间距离的新指标及其相关度量。所提出的指标和度量均基于Hausdorff距离,可用于不确定区间数据的聚类。然后利用新度量引入了区间聚类的聚类方法。最后,通过实验验证了该方法的有效性。结果表明,该方法可以有效地识别出合适的聚类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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