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What is Clustering-Based Outlier Detection Methods about?
Clustering-based approaches to outlier detection identify outliers by examining the relationship between objects and clusters, using methods such as determining if an object belongs to any cluster, measuring distance to the nearest cluster, or identifying small clusters. Techniques like the FindCBLOF algorithm assess the similarity of data points to clusters to classify outliers, while also addressing computational efficiency. These methods are advantageous for their unsupervised nature and ability to handl
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