Approximation spaces in machine learning and pattern recognition

Authors:
Andrzej Skowron;Jarosław Stepaniuk;Roman Swiniarski
Affiliations:
Institute of Mathematics, Warsaw University, Warsaw, Poland;Department of Computer Science, Białystok University of Technology, Białystok, Poland;Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland
Venue:
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Year:
2005

Variable precision rough set model

Journal of Computer and System Sciences
Tolerance approximation spaces

Fundamenta Informaticae - Special issue: rough sets
Rough Sets: Theoretical Aspects of Reasoning about Data

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Handbook on Ontologies (International Handbooks on Information Systems)

Handbook on Ontologies (International Handbooks on Information Systems)
Complex Patterns

Fundamenta Informaticae - Concurrency Specification and Programming (CS&P 2003)
Approximation spaces and information granulation

Transactions on Rough Sets III

Distributed learning with data reduction

Transactions on computational collective intelligence IV

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Approximation spaces are fundamental for the rough set approach. We discuss their application in machine learning and pattern recognition.