Mining incomplete data: a rough set approach

Authors:
Jerzy W. Grzymala-Busse
Affiliations:
Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS and Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland
Venue:
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Year:
2011

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Abstract

A rough set approach to mining incomplete data is presented in this paper. Our main tool is an attribute-value pair block. A characteristic set, a generalization of the elementary set well-known in rough set theory, may be computed using such blocks. For incomplete data sets three different types of global approximations: singleton, subset and concept are defined. Additionally, for incomplete data sets a local approximation is defined as well.