Demonstrates a new measure for assessing cluster separation, aiding in data partitioning and algorithm development.
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.
No takes yet. Share an insight, caveat, or question.
Davies et al. (1979) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:
More from IEEE Transactions on Pattern Analysis and Machine Intelligence