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题名: Evaluating accuracy of community detection using the relative normalized mutual information
作者: Zhang, P
刊名: JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
出版日期: 2015
期号: 0, 页码:P11006
关键词: random graphs ;  networks ;  clustering techniques
学科分类: Mechanics ;  Physics
DOI: http://dx.doi.org/10.1088/1742-5468/2015/11/P11006
通讯作者: Zhang, P (reprint author), Chinese Acad Sci, State Key Lab Theoret Phys, Inst Theoret Phys, Beijing 100190, Peoples R China.
文章类型: Article
英文摘要: The normalized mutual information (NMI) has been widely used to evaluate the accuracy of community detection algorithms. However in this article we show that the NMI is seriously affected by systematic errors due to finite size of networks, and may give a wrong estimate of performance of algorithms in some cases. We give a simple theory to the finite-size effect of NMI and test our theory numerically. Then we propose a new metric for the accuracy of community detection, namely the relative normalized mutual information (rNMI), which considers statistical significance of the NMI by comparing it with the expected NMI of random partitions. Our numerical experiments show that the rNMI overcomes the finite-size effect of the NMI.
类目[WOS]: Mechanics ;  Physics, Mathematical
关键词[WOS]: NETWORKS
收录类别: SCI
项目资助者: Santa Fe Institute
语种: 英语
Citation statistics: 
内容类型: 期刊论文
URI标识: http://ir.itp.ac.cn/handle/311006/20803
Appears in Collections:理论物理所2015年知识产出_期刊论文

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Recommended Citation:
Zhang, P. Evaluating accuracy of community detection using the relative normalized mutual information[J]. JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT,2015(0):P11006.
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