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Attribute reduction with discernibility matrix approaches

Authors: null Lishi Zhang; null Shengzhe Gao;

Attribute reduction with discernibility matrix approaches

Abstract

With the large number of attributes, reduction of its attributes is a crucial step in the clustering analysis of data The main task of the present work is to construct a novel clustering analysis method motivated by the fundamental idea from information system, the computer simulation shows that the reduction of attributes gives a better accuracy of clustering rate.

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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!
0
Average
Average
Average
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