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A new approach to mining fuzzy databases using nearest neighbor classification by exploiting attribute hierarchies

✍ Scribed by Supriya Kumar De; P. Radha Krishna


Publisher
John Wiley and Sons
Year
2004
Tongue
English
Weight
112 KB
Volume
19
Category
Article
ISSN
0884-8173

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✦ Synopsis


Data classification is a well-organized operation in the field of data mining. This article presents an application of the k-nearest neighbor classification technique for mining a fuzzy database. We consider a data set in which attribute values have certain similarities in nature and analyze the observations for the domain of each attribute, on the basis of fuzzy similarity relations. The proposed technique is general and the presented case study demonstrates the suitability of using this fuzzy approach for mining fuzzy databases, especially when the database contains various levels of abstraction.