Bat algorithm for rough set attribute reduction
Attribute reduction (AR) refers to the problem of choosing an optimal subset of attributes from a larger set of possible attributes that are most predictive for a given result. AR techniques have recently attracted attention due to its importance in many areas such as pattern recognition, machine le...
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2023
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my.uniten.dspace-302002023-12-29T15:45:27Z Bat algorithm for rough set attribute reduction Taha A.M. Tang A.Y.C. 55699699200 36806985400 Attribute reduction Bat algorithm Nature inspired Rough set Attribute reduction (AR) refers to the problem of choosing an optimal subset of attributes from a larger set of possible attributes that are most predictive for a given result. AR techniques have recently attracted attention due to its importance in many areas such as pattern recognition, machine learning and signal processing. In this paper, a new optimization method has been introduced called bat algorithm for attribute reduction (BAAR), the proposed method is based mainly on the echolocation behavior of bats. BAAR is verified using 13 benchmark datasets. Experimental results show that the performances of the proposed method when compared to other features selection methods achieve equal or better performance. � 2005 - 2013 JATIT & LLS. All rights reserved. Final 2023-12-29T07:45:27Z 2023-12-29T07:45:27Z 2013 Article 2-s2.0-84877748909 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84877748909&partnerID=40&md5=c7a7697d1cd210ff8db1aef91ab51fb1 https://irepository.uniten.edu.my/handle/123456789/30200 51 1 1 8 Asian Research Publishing Network (ARPN) Scopus |
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Universiti Tenaga Nasional |
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UNITEN Library |
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Asia |
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Malaysia |
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Universiti Tenaga Nasional |
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UNITEN Institutional Repository |
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http://dspace.uniten.edu.my/ |
| topic |
Attribute reduction Bat algorithm Nature inspired Rough set |
| spellingShingle |
Attribute reduction Bat algorithm Nature inspired Rough set Taha A.M. Tang A.Y.C. Bat algorithm for rough set attribute reduction |
| description |
Attribute reduction (AR) refers to the problem of choosing an optimal subset of attributes from a larger set of possible attributes that are most predictive for a given result. AR techniques have recently attracted attention due to its importance in many areas such as pattern recognition, machine learning and signal processing. In this paper, a new optimization method has been introduced called bat algorithm for attribute reduction (BAAR), the proposed method is based mainly on the echolocation behavior of bats. BAAR is verified using 13 benchmark datasets. Experimental results show that the performances of the proposed method when compared to other features selection methods achieve equal or better performance. � 2005 - 2013 JATIT & LLS. All rights reserved. |
| author2 |
55699699200 |
| author_facet |
55699699200 Taha A.M. Tang A.Y.C. |
| format |
Article |
| author |
Taha A.M. Tang A.Y.C. |
| author_sort |
Taha A.M. |
| title |
Bat algorithm for rough set attribute reduction |
| title_short |
Bat algorithm for rough set attribute reduction |
| title_full |
Bat algorithm for rough set attribute reduction |
| title_fullStr |
Bat algorithm for rough set attribute reduction |
| title_full_unstemmed |
Bat algorithm for rough set attribute reduction |
| title_sort |
bat algorithm for rough set attribute reduction |
| publisher |
Asian Research Publishing Network (ARPN) |
| publishDate |
2023 |
| _version_ |
1806424376649711616 |
| score |
13.251813 |