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Estimating the number of data clusters via the contrast statistic
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作者 Yuriy Lyakh vitaliy gurianov +1 位作者 Oleg Gorshkov Yuriy Vihovanets 《Journal of Biomedical Science and Engineering》 2012年第2期95-99,共5页
A new method (the Contrast statistic) for estimating the number of clusters in a set of data is proposed. The technique uses the output of self-organising map clustering algorithm, comparing the change in dependency ... A new method (the Contrast statistic) for estimating the number of clusters in a set of data is proposed. The technique uses the output of self-organising map clustering algorithm, comparing the change in dependency of “Contrast” value upon clusters number to that expected under a uniform distribution. A simulation study shows that the Contrast statistic can be used successfully either, when variables describing the object in a multi-dimensional space are independent (ideal objects) or dependent (real biological objects). 展开更多
关键词 SOM NEURAL Network Clustering Gap Statistic SILHOUETTE Statistic
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