A cluster separation measure
DL Davies, DW Bouldin - IEEE transactions on pattern analysis …, 1979 - ieeexplore.ieee.org
DL Davies, DW Bouldin
IEEE transactions on pattern analysis and machine intelligence, 1979•ieeexplore.ieee.orgA 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.
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.
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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