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Dual-random ensemble method for multi-label classification of biological data
conference contributionposted on 2009-01-01, 00:00 authored by Gulisong NasierdingGulisong Nasierding, B Duc, Alycia LeeAlycia Lee, Abbas KouzaniAbbas Kouzani
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.