Cluster-Based Outlier Detection is a method for identifying anomalies by distinguishing data points that reside in low-density regions or deviate significantly from established cluster structures, thereby differentiating it from other outlier detection techniques through its reliance on cluster formation and intra-cluster distance analysis.
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565
Clustering by fast search and find of density peaks
Álex Rodríguez, Alessandro Laio · Science · 2014 · 5K citations
Computing, Astronomy, Bioinformatics +13
Discovering cluster-based local outliers
Zengyou He, Xiaofei Xu, Shengchun Deng · Pattern Recognition Letters · 2003 · 1K citations
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Amirkabir University of Technology
Tehran, Iran
9 h-index
16 publications
894 citations
Chinese Academy of Sciences
Beijing, China
7 h-index
18 publications
1K citations
Harbin Institute of Technology
Harbin, China
7 h-index
13 publications
5.3K citations
University of Missouri
Columbia, United States
7 h-index
20 publications
812 citations
Polish Academy of Sciences
Warsaw, Poland
6 h-index
13 publications
494 citations
The University of Melbourne
Melbourne, Australia
6 h-index
19 publications
1K citations
Chongqing University
Chongqing, China
5 h-index
16 publications
936 citations
Guru Gobind Singh Indraprastha University
Delhi, India
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8 publications
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