构建系统发育树的分层聚类方法

C. Kandemir-Cavas, E. Nasibov
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引用次数: 4

摘要

层次聚类算法是构建蛋白质序列系统发育树的常用算法。分层聚类是数据点的递归聚类。相似度是通过测量元素之间的距离来计算的。数据之间的关系用树形图直观地表示。单连杆、平均连杆、完全连杆和沃德连杆是常用的几种分层聚类算法。本文提出了一种基于有序加权平均(OWA)聚集算子的蛋白质分层聚类簇间距离求解方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Alternative hierarchical clustering approach in construction of phylogenetic trees
Hierarchical clustering algorithms are frequently used in constructing phylogenetic trees of protein sequences. Hierarchical clustering is the recursive clustering of data points. Similarity is computed by measuring the distance between elements. Relationship between data is visually denoted by dendrogram. Single linkage, average linkage, complete linkage and Ward's linkage are some of frequently used hierarchical clustering algorithms. In this study, an alternative solution based on Ordered Weighted Average (OWA) aggregation operator is proposed in solving distance between clusters in hierarchical clustering of proteins.
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