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Dual-random ensemble method for multi-label classification of biological data

Nasierding, G., Duc, B. V., Lee, S. L. A. and Kouzani, Abbas Z. 2009, Dual-random ensemble method for multi-label classification of biological data, in ISBB 2009 : Proceedings of the 2009 International Symposium on Bioelectronics and Bioinformatics, ISBB, Melbourne, Vic., pp. 49-52.

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Title Dual-random ensemble method for multi-label classification of biological data
Author(s) Nasierding, G.
Duc, B. V.
Lee, S. L. A.
Kouzani, Abbas Z.
Conference name Bioelectronics and Bioinformatics. Symposium (2009 : Melbourme, Victoria)
Conference location Melbourne, Victoria
Conference dates 9-11 Dec. 2009
Title of proceedings ISBB 2009 : Proceedings of the 2009 International Symposium on Bioelectronics and Bioinformatics
Editor(s) [Unknown]
Publication date 2009
Conference series Bioelectronics and Bioinformatics Symposium
Start page 49
End page 52
Total pages 4
Publisher ISBB
Place of publication Melbourne, Vic.
Summary This paper presents a dual-random ensemble multi-label classification method for classification of multi-label data. The method is formed by integrating and extending the concepts of feature subspace method and random k-label set ensemble multi-label classification method. Experiemental results show that the developed method outperforms the exisiting multi-lable classification methods on three different multi-lable datasets including the biological yeast and genbase datasets.

Language eng
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 890402 Film and Video Services (excl. Animation and Computer Generated Imagery)
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2009, ISBB
Persistent URL http://hdl.handle.net/10536/DRO/DU:30029219

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.