MCDMClustering Validation

Davies-Bouldin Index

The Davies-Bouldin Index, introduced by Davies and Bouldin in 1979, is a metric for evaluating clustering quality based on the average similarity between each cluster and its most similar neighboring cluster. Lower values indicate better clustering, with a minimum of 0 representing perfectly separated, non-overlapping clusters.

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Sources

  1. Davies, D. L., & Bouldin, D. W. (1979). A cluster separation measure. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1(2), 224-227. DOI: 10.1109/TPAMI.1979.4766909

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Referenced by

ScholarGateDavies-Bouldin Index (Davies-Bouldin Index for Cluster Separation). Retrieved 2026-06-04 from https://scholargate.app/en/model-evaluation/davies-bouldin-index