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Procedia Engineering
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Procedia Engineering
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The Improved Partition Coefficient

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2011 English Publisher:Elsevier BVJournal:Procedia Engineering, volume 24, pages 534-538 (issn: 1877-7058, Copyright policy )
Authors: Li, Chun sheng;

doi: 10.1016/j.proeng.2011.11.2691

The Improved Partition Coefficient

Abstract

AbstractThis paper proposed an improved partition coefficient (IPC) index by turning two disadvantages of partition coefficient (PC) index into advantages. Comparisons between IPC index and PC index and two existed cluster validity indexes are conducted on four real data sets. Experimental results show that IPC is able to identify the cluster number underlying the data set in the case that PC index is unable to do and outperforms the two existed cluster validity indexes.

Related Organizations
Keywords

fuzzy clustering, partition coefficient, Engineering(all), cluster number

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Top 10%
Average
gold