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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ISBB 2009 : Proceedings of the 2009 International Symposium on Bioelectronics and Bioinformatics
Bioelectronics and Bioinformatics Symposium
Place of publication
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.
Field of Research
080109 Pattern Recognition and Data Mining
Socio Economic Objective
890402 Film and Video Services (excl. Animation and Computer Generated Imagery)
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