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A Cluster Separation Measure

David L. Davies; Donald W. Bouldin · IEEE Transactions on Pattern Analysis and Machine Intelligence · 1979

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Author / responsible party
David L. Davies; Donald W. Bouldin
Publisher
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year
1979
Language
English

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A measure is presented which indicates the similarity of clusters which are assumed to have a data density which is a decreasing function of distance from a vector characteristic of the cluster. The measure can be used to infer the appropriateness of data partitions and can therefore be used to compare relative appropriateness of various divisions of the data. The measure does not depend on either the number of clusters analyzed nor the method of partitioning of the data and can be used to guide a cluster seeking algorithm.

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APA 7

Davies, D. L. & Bouldin, D. W. (1979). A Cluster Separation Measure. https://doi.org/10.1109/tpami.1979.4766909

MLA

Davies, David L, and Donald W. Bouldin. "A Cluster Separation Measure." 1979. https://doi.org/10.1109/tpami.1979.4766909.

Chicago

Davies, David L. and Donald W. Bouldin. 1979. "A Cluster Separation Measure.". https://doi.org/10.1109/tpami.1979.4766909.

Harvard

Davies, D. L. and Bouldin, D. W. 1979, A Cluster Separation Measure, IEEE Transactions on Pattern Analysis and Machine Intelligence, available at: https://doi.org/10.1109/tpami.1979.4766909 [Accessed 8 Aug. 2026].

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Resource details

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Title
A Cluster Separation Measure
Author / contributors
David L. Davies; Donald W. Bouldin
Publisher
IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication year
1979
Language
English

Subjects

Explore related resources through these subjects.

Measure (data warehouse); Cluster (spacecraft); Similarity measure; Computer science; Data mining; Artificial intelligence; Pattern recognition (psychology); Similarity (geometry); Function (biology); Separation (statistics); Mathematics; Machine learning
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