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A Cluster Separation Measure
February 1979 (vol. 1 no. 2)
pp. 224-227
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.
Index Terms:
Dispersion,Density measurement,Algorithm design and analysis,Clustering algorithms,Partitioning algorithms,Multidimensional systems,Data analysis,Performance analysis,Humans,Missiles,similarity measure,Cluster,data partitions,multidimensional data analysis,parametric clustering,partitions
"A Cluster Separation Measure," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 1, no. 2, pp. 224-227, Feb. 1979, doi:10.1109/TPAMI.1979.4766909
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