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On feature selection via rough sets

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Computer Analysis of Images and Patterns (CAIP 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 970))

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Abstract

The paper presents a critical comment on the rough sets approach to feature selection. It is highlighted that the small sample size may lead to spurious results in evaluating the feature subsets. Along with this, some attractive advantages of rough sets criteria are emphasized, and a new criterion is proposed. Two examples have been generated in order to demonstrate the flexibility of the proposed criterion and its advantages over some conventional criteria.

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Václav Hlaváč Radim Šára

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© 1995 Springer-Verlag Berlin Heidelberg

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Kuncheva, L.I., Kounchev, R.K. (1995). On feature selection via rough sets. In: Hlaváč, V., Šára, R. (eds) Computer Analysis of Images and Patterns. CAIP 1995. Lecture Notes in Computer Science, vol 970. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60268-2_355

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  • DOI: https://doi.org/10.1007/3-540-60268-2_355

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60268-2

  • Online ISBN: 978-3-540-44781-8

  • eBook Packages: Springer Book Archive

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