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Clustering-Based Outlier Detection (3): Detecting Outliers in Small Clusters

  • FindCBLOF: Detect outliers in small clusters
    • Find clusters, and sort them in decreasing size
    • To each data point, assign a cluster-based local outlier factor (CBLOF):
    • If obj p belongs to a large cluster, CBLOF = cluster_size X similarity between p and cluster
    • If p belongs to a small one, CBLOF = cluster size X similarity betw. p and the closest large cluster

  • Clustering-Based Outlier Detection (3): Detecting Outliers in Small Clusters
  • Ex. In the figure, o is outlier since its closest large cluster is C1, but the similarity between o and C1 is small. For any point in C3, its closest large cluster is C2 but its similarity from C2 is low, plus |C3| = 3 is small


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