Local contrast as an effective means to robust clustering against varying densities

Most density-based clustering methods have difficulties detecting clusters of hugely different densities in a dataset. A recent density-based clustering CFSFDP appears to have mitigated the issue. However, through formalising the condition under which it fails, we reveal that CFSFDP still has the sa...

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Veröffentlicht in:	Machine learning 2018-09, Vol.107 (8-10), p.1621-1645
Hauptverfasser:	Chen, Bo, Ting, Kai Ming, Washio, Takashi, Zhu, Ye
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial Intelligence Clustering Clusters Computer Science Control Density Mechatronics Natural Language Processing (NLP) Robotics Simulation and Modeling Special Issue of the ECML PKDD 2018 Journal Track
Online-Zugang:	Volltext
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