Feature Subset Selection Using Differential Evolution

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dc.contributor.author Khushaba, Rami en_US
dc.contributor.author Al-Ani, Ahmed en_US
dc.contributor.author Al-Jumaily, Adel Ali en_US
dc.contributor.editor en_US
dc.contributor.editor Mario Koppen, Nikola Kasabov, and George Coghill en_US
dc.date.accessioned 2010-05-28T09:38:04Z
dc.date.available 2010-05-28T09:38:04Z
dc.date.issued 2009 en_US
dc.identifier 2009003037 en_US
dc.identifier.citation Khushaba Rami N, Al-Ani Ahmed, and Al-Jumaily Adel 2009, 'Feature Subset Selection Using Differential Evolution', in http://dx.doi.org/10.1007/978-3-642-02490-0_13 (ed.), Springer Berlin / Heidelberg, Germany, pp. 103-110. en_US
dc.identifier.issn 978-3-642-02489-4 en_US
dc.identifier.other B1 en_US
dc.identifier.uri http://hdl.handle.net/10453/7833
dc.description.abstract One of the fundamental motivations for feature selection is to overcome the curse of dimensionality. A novel feature selection algorithm is developed in this chapter based on a combination of Differential Evolution (DE) optimization technique and statistical feature distribution measures. The new algorithm, referred to as DEFS, utilizes the DE float number optimizer in a combinatorial optimization problem like feature selection. The proposed DEFS highly reduces the computational cost while at the same time proves to present a powerful performance. The DEFS is tested as a search procedure on different datasets with varying dimensionality. Practical results indicate the significance of the proposed DEFS in terms of solutions optimality and memory requirements. en_US
dc.language en_US
dc.publisher Springer en_US
dc.relation.isbasedon http://dx.doi.org/10.1007/978-3-642-02490-0_13 en_US
dc.title Feature Subset Selection Using Differential Evolution en_US
dc.parent Advances in Neuro-Information Processing - Lecture Notes in Computer Science en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Germany en_US
dc.identifier.startpage 103 en_US
dc.identifier.endpage 110 en_US
dc.cauo.name FEIT.School of Elec, Mech and Mechatronic Systems en_US
dc.conference Verified OK en_US
dc.for 080109 en_US
dc.personcode 101188 en_US
dc.personcode 040052 en_US
dc.personcode 011083 en_US
dc.percentage 40 en_US
dc.classification.name Pattern Recognition and Data Mining en_US
dc.classification.type FOR-08 en_US
dc.edition First Edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords en_US
dc.staffid en_US
dc.staffid 011083 en_US


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