Interval-valued Fuzzy-Rough Feature Selection in Datasets with Missing Values

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

14 Dyfyniadau(SciVal)
218 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 principle 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
TeitlProceedings of the 18th International Conference on Fuzzy Systems
Tudalennau610-615
Nifer y tudalennau6
ISBN (Electronig)978-1-4244-3597-5
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 2009
DigwyddiadFuzzy Systems - Jeju Island, Korea (Gweriniaeth)
Hyd: 20 Awst 200924 Awst 2009
Rhif y gynhadledd: 18

Cynhadledd

CynhadleddFuzzy Systems
Teitl crynoFUZZ-IEEE-2009
Gwlad/TiriogaethKorea (Gweriniaeth)
DinasJeju Island
Cyfnod20 Awst 200924 Awst 2009

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