A fast density-based data stream clustering algorithm with cluster centers self-determined for mixed data

Most data streams encountered in real life are data objects with mixed numerical and categorical attributes. Currently most data stream algorithms have shortcomings including low clustering quality, difficulties in determining cluster centers, poor ability for dealing with outliers’ issue. A fast de...

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Veröffentlicht in:	Information sciences 2016-06, Vol.345, p.271-293
Hauptverfasser:	Chen, Jin-Yin, He, Hui-Hao
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Clustering Clusters Data mining Data stream clustering Data transmission Graphs Mathematical analysis Mixed attributes Mixed distance measure metrics Peak field intensity Regression analysis
Online-Zugang:	Volltext
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