Distance Based Attribute Reduction in Set-Valued Decision Tables

Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
The rough set theory proposed by the researchers is an effective tool to solve attribute reduction problems and to extract rules in single-valued information systems. Rough set based attribute reduction is an important problem in pre-processing step in data mining. However, most rough set based attribute reduction methods perform on single-value decision tables. In this paper, they solve attribute reduction problems in set-valued decision tables. Their method uses the distance measure which constructed between a conditional attribute set and decision attribute.

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