Dynamic feature selection with fuzzy-rough sets

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

10 Dyfyniadau(SciVal)

Crynodeb

Various strategies have been exploited for the task of feature selection, in an effort to identify more compact and better quality feature subsets. Most existing approaches focus on selecting from a static pool of training instances with a fixed number of original features. However, in practice, data may be gradually refined, and information regarding the problem domain may be actively added or removed. In this paper, a technique based on fuzzy-rough sets is extended to support dynamic feature selection. The proposed method is capable of carrying out on-line selection with incrementally added features or instances. Also, the cases of feature or instance removal are investigated. This brings a novel and beneficial addition to the current research in feature selection. Four possible dynamic selection scenarios are considered, with algorithms proposed in order to handle such individual situations. Simulated experimentation is carried out using real world benchmark data sets, in order to demonstrate the efficacy of the proposed work.
Iaith wreiddiolSaesneg
TeitlProceedings of the 22nd International Conference on Fuzzy Systems
CyhoeddwrIEEE Press
Tudalennau1-7
Nifer y tudalennau7
ISBN (Argraffiad)978-1-4799-0020-6
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 2013
DigwyddiadFuzzy Systems - Hyderabad, Hyderabad, India
Hyd: 07 Gorff 201310 Gorff 2013
Rhif y gynhadledd: 22

Cynhadledd

CynhadleddFuzzy Systems
Teitl crynoFUZZ-IEEE-2013
Gwlad/TiriogaethIndia
DinasHyderabad
Cyfnod07 Gorff 201310 Gorff 2013

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