Rough Sets: Mathematical Foundations

By L. Polkowski. 2002

404 citations recorded by the source corpus.

How researchers see this paper

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Computational Intelligence and Feature Selection - Rough and Fuzzy Approaches (2008, methodology): “Rough set theory (RST) can be used as such a tool to discover data dependencies and to reduce the number of attributes contained in a dataset using the data alone, requiring no additional information [261,274,323].”
Rudiments of rough sets (2007, background): “, [28,33,44,48,74,97,112,113,131,182,194,195,206,237,241,244,245,272,305,374]), issues of the Transactions on Rough Sets [225–228], special issues of other journals (see, e.”
Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches (2004, methodology): “Rough set theory (RST) can be used as such a tool to discover data dependencies and to reduce the number of attributes contained in a data set using the data alone and no additional information [38], [41].”
New Approaches to Fuzzy-Rough Feature Selection (2009, background): “Other such techniques may be found in [21] and [22].”