区间型-2模糊c均值协同聚类方法

Trong Hop Dang, L. Ngo, W. Pedrycz
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引用次数: 13

摘要

关于FCM算法在聚类和协同聚类中的应用,特别是在数据分析、数据挖掘和模式识别等方面的研究已经非常多。本文提出了一种利用区间2型模糊集实现协同聚类的新方法。在一个数据站点实现聚类结果的数据会影响在其他数据站点进行的聚类。这些方法赋予区间2型模糊集有助于处理数据中存在的不确定性。与以前的方法相比,用天气数据集进行的实验显示出更好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interval Type-2 fuzzy C-Means approach to collaborative clustering
There have been numerous studies on using the FCM algorithm in clustering and collaboration clustering, especially in data analysis, data mining and pattern recognition. In this study, we present new methods involving interval Type-2 fuzzy sets to realize collaborative clustering. Data in which the clustering results realized at one data site impact clustering carried out at other data sites. Those methods endowed with interval type-2 fuzzy sets help cope with uncertainties present in data. The experiment with weather data sets has shown better results in comparison with the previous approaches.
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