MS2OD: outlier detection using minimum spanning tree and medoid selection

MS2OD: outlier detection using minimum spanning tree and medoid selection

As an essential task in data mining, outlier detection identifies abnormal patterns in numerous applications, among which clustering-based outlier detection is one of the most popular methods for its effectiveness in detecting cluster-related outliers, especially in medical applications. This articl...

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Bibliographic Details
Main Authors: Jia Li, Jiangwei Li, Chenxu Wang, Fons J Verbeek, Tanja Schultz, Hui Liu
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:Machine Learning: Science and Technology
Subjects:
outlier detection
data mining
medical data
machine learning
clustering
minimum spanning tree
Online Access:https://doi.org/10.1088/2632-2153/ad2492

Internet

https://doi.org/10.1088/2632-2153/ad2492

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