Dual-random ensemble method for multi-label classification of biological data
Gulisong Nasierding, B. Duc, S. L. A. Lee, Abbas Z. Kouzani · 2009
This paper presents a dual-random ensemble multi-label classification method for classification of multilabel 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. Experimental results show that the developed method outperforms the existing multi-label classification methods on three different multi-label datasets including the biological yeast and genbase datasets.