Incomplete Information Tables and Rough Classification

@article{Stefanowski2001IncompleteIT,
  title={Incomplete Information Tables and Rough Classification},
  author={Jerzy Stefanowski and Alexis Tsouki{\'a}s},
  journal={Computational Intelligence},
  year={2001},
  volume={17}
}
The rough set theory, based on the original definition of the indiscernibility relation, is not useful for analysing incomplete information tables where some values of attributes are unknown. In this paper we distinguish two different semantics for incomplete information: the “missing value” semantics and the “absent value” semantics. The already known approaches, e.g. based on the tolerance relations, deal with the missing value case. We introduce two generalisations of the rough sets theory… 

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