Summary
A new approach to missing attribute values, based on the idea of an attribute-concept value, is studied in the paper. This approach, together with two other approaches to missing attribute values, based on “do not care” conditions and lost values are discussed using rough set methodology, including attribute-value pair blocks, characteristic sets, and characteristic relations. Characteristic sets are generalization of elementary sets while characteristic relations are generalization of the indiscernibility relation. Additionally, three definitions of lower and upper approximations are discussed and used for induction of certain and possible rules.
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Grzymala-Busse, J.W. (2008). Three Approaches to Missing Attribute Values: A Rough Set Perspective. In: Lin, T.Y., Xie, Y., Wasilewska, A., Liau, CJ. (eds) Data Mining: Foundations and Practice. Studies in Computational Intelligence, vol 118. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78488-3_8
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DOI: https://doi.org/10.1007/978-3-540-78488-3_8
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