利用k-均值目标函数生成平衡结构的广义方法

Q3 Medicine
Shivani Gupta, Aaditya Jain, Priyanka Jeswani
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引用次数: 2

摘要

在某些应用程序中需要平衡的结构,而集群本身并不以生成平衡的数据分区为目标。我们需要做两件事:平衡的定义和调整目标函数以适应这一定义。本文提出了聚类平衡的三种定义:基数、方差和密度;这样它们就可以直接解释为平衡集群的应用程序。这些与标准k-means算法的目标函数相结合,以证明在流行数据集上输出平衡的效果。本文还提出了衡量任何集群结构平衡系数的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generalized Method to Produce Balanced Structures Through k-means Objective Function
Balanced structures are required in certain applications and clustering does not inherently aim at producing balanced partition of data. Two things are essentially required: definition of balance and modification to objective function to accommodate this definition. This paper proposes three definitions of balance in clusters: cardinality, variance and density; such that they can be directly interpreted for applications of balanced clustering. These are incorporated with objective function of standard k-means algorithm to demonstrate effect of balance in output over popular datasets. Paper also suggests method to measure the balance factor of any cluster structure.
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来源期刊
Koomesh
Koomesh Medicine-Medicine (all)
CiteScore
0.80
自引率
0.00%
发文量
0
审稿时长
24 weeks
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