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Metasample-Based Robust Sparse Representation for Tumor Classification 被引量:1
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作者 Bin Gan Chun-Hou Zheng Jin-Xing Liu 《Engineering(科研)》 2013年第5期78-83,共6页
In this paper, based on sparse representation classification and robust thought, we propose a new classifier, named MRSRC (Metasample Based Robust Sparse Representation Classificatier), for DNA microarray data classif... In this paper, based on sparse representation classification and robust thought, we propose a new classifier, named MRSRC (Metasample Based Robust Sparse Representation Classificatier), for DNA microarray data classification. Firstly, we extract Metasample from trainning sample. Secondly, a weighted matrix W is added to solve an l1-regular- ized least square problem. Finally, the testing sample is classified according to the sparsity coefficient vector of it. The experimental results on the DNA microarray data classification prove that the proposed algorithm is efficient. 展开更多
关键词 DNA MICROARRAY DATA SPARSE REPRESENTATION CLASSIFICATION mrsrc ROBUST
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