Interval-valued Fuzzy-Rough Feature Selection and Application for Handling Missing Values in Datasets

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddTrafodion Cynhadledd (Nid-Cyfnodolyn fathau)

27 Wedi eu Llwytho i Lawr (Pure)

Crynodeb

One of the many successful applications of rough set theory has been to the area of feature selection. The rough set ideology of using only the supplied data and no other information has many benefits, where most other methods require supplementary knowledge. Fuzzy-rough set theory has recently been proposed as an extension of this, in order to better handle the uncertainty present in real data. However, following this approach, there has been no investigation (theoretical or otherwise) into how to deal with missing values effectively, another problem encountered when using real world data. This paper proposes an extension of the fuzzy-rough feature selection methodology, based on interval-valued fuzzy sets, as a means to counter this problem via the representation of missing values in an intuitive way.
Iaith wreiddiolSaesneg
Teitl8th Annual UK Workshop on Computational Intelligence (UKCI'08)
Tudalennau59-64
Nifer y tudalennau6
StatwsCyhoeddwyd - 2008
Digwyddiad8th Annual UK Workshop on Computational Intelligence (UKCI'08) - Leicester, Teyrnas Unedig Prydain Fawr a Gogledd Iwerddon
Hyd: 10 Medi 200812 Medi 2008

Cynhadledd

Cynhadledd8th Annual UK Workshop on Computational Intelligence (UKCI'08)
Gwlad/TiriogaethTeyrnas Unedig Prydain Fawr a Gogledd Iwerddon
DinasLeicester
Cyfnod10 Medi 200812 Medi 2008

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