A comparison study of similarity measures for covering-based neighborhood classifiers

Inf. Sci., Volume 448-449, 2018, Pages 1-17.

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Abstract:

Abstract In data mining, neighborhood classifiers are valid not only for numeric data but also symbolic data. The key issue for a neighborhood classifier is how to measure the similarity between two instances. In this paper, we compare six similarity measures, Overlap, Eskin , occurrence frequency ( OF ), inverse OF ( IOF ), Goodall3 ...More

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