Abstract The conventional clustering approaches are not very effective in dealing with clusters having overlapping regions. The three-way clustering (3WC) is an effective and promising approach in this regards. A key issue in 3WC is the determination of thresholds which plays a crucial and important role in accurate estimation of the overlapping region. In this article, we propose different variance based criteria for determining the thresholds. In particular, we examine the variance or spread in evaluation function values of objects contained in the three regions obtained with 3WC of objects. An algorithm called 3WC-OR is introduced that considers the optimization of the proposed criteria for determining effective thresholds by incorporating approaches such as genetic algorithms and game-theoretic rough sets. Experimental results on five UCI datasets indicate that the proposed algorithm significantly improves results on datasets with overlapping clusters and provide comparable results on datasets with non-overlapping clusters.

中文翻译：

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处理重叠聚类的基于方差的三向聚类方法

摘要 传统的聚类方法在处理具有重叠区域的聚类时不是很有效。在这方面，三向聚类（3WC）是一种有效且有前景的方法。3WC 中的一个关键问题是阈值的确定，这在准确估计重叠区域中起着至关重要的作用。在本文中，我们提出了不同的基于方差的标准来确定阈值。特别是，我们检查了用对象的 3WC 获得的三个区域中包含的对象的评估函数值的方差或扩散。引入了一种称为 3WC-OR 的算法，该算法通过结合遗传算法和博弈论粗糙集等方法来考虑对确定有效阈值的建议标准进行优化。