Discovering Classification Knowledge in Databases Using Rough Sets

Ning Shan, Wojciech Ziarko, Howard J. Hamilton, Nick Cercone

The paper presents an approach to data mining involving search for complete, or nearly complete, domain classifications in terms of attribute values. Our objective is to find classifications based on interacting attributes that provide a good characterization of the concept of interest by maximizing predefined quality criteria. The paper introduces the notion of the classification complexity and several other measures to evaluate quality.

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