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Evaluation of pattern recognition methods by criteria based on information theory and euclidean geometry

✍ Scribed by Dietrich Wienke; Klaus Danzer

Publisher: Elsevier Science
Year: 1986
Tongue: English
Weight: 580 KB
Volume: 184
Category: Article
ISSN: 0003-2670
DOI: 10.1016/s0003-2670(00)86474-0

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✦ Synopsis

Euclidean geometry and information and fuzzy-set theory are used to develop general criteria for the evaluation of clustering methods. A separation function, describing the geometric clustering in a feature space for a given separation state, is introduced. Suitable clustering algorithms for given data can be selected by using the measure derived. The criteria developed are used in studies of the homogeneity of solids.

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