Approximation Spaces in RoughGranular Computing

We discuss some generalizations of the approximation space definition introduced in 1994 [24, 25]. These generalizations are motivated by real-life applications. Rough set based strategies for extension of such generalized approximation spaces from samples of objects onto their extensions are discus...

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Published inFundamenta informaticae Vol. 100; no. 1-4; pp. 141 - 157
Main Authors Skowron, Andrzej, Stepaniuk, Jarosaw, Swiniarski, Roman
Format Journal Article
LanguageEnglish
Published 01.01.2010
Subjects
Approximation
Foundations
Granular materials
Granules
Intelligence
Machine learning
Mathematical analysis
Strategy
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Summary:We discuss some generalizations of the approximation space definition introduced in 1994 [24, 25]. These generalizations are motivated by real-life applications. Rough set based strategies for extension of such generalized approximation spaces from samples of objects onto their extensions are discussed. This enables us to present the uniform foundations for inducing approximations of different kinds of granules such as concepts, classifications, or functions. In particular, we emphasize the fundamental role of approximation spaces for inducing diverse kinds of classifiers used in machine learning or data mining.
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ISSN:0169-2968