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| Gene Expression Data Clustering Based on Projection Least Square Regression Subspace Segmentation |
| JIAN Cai-Ren, CHEN Xiao-Yun |
| College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108 |
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Abstract Subspace segmentation method is an important method for machine learning. The existing researches on subspace segmentation method are generally on the original sample space. Advanced by existing dimensional reduction methods, a gene expression data clustering method based on projection subspace segmentation is proposed by joining projection method and least square regression based subspace segmentation. Projection matrix and remodeling matrix is got by using alternate optimization, and dimension reduction and cluster is realized simultaneously. The experimental results on six gene expression datasets illustrate the validity of the proposed method.
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Received: 28 May 2014
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2015, Vol. 28 
