Microarray techniques have been used to delineate cancer groups or to identify candidate genes for cancer prognosis. As such problems can be viewed as classification ones, various classification methods have been applied to analyze or interpret gene expression data. In this paper, we propose a novel method based on robust principal component analysis (RPCA) to classify tumor samples of gene expression data. Firstly, RPCA is utilized to highlight the characteristic genes associated with a special biological process. Then, RPCA and RPCA+LDA (robust principal component analysis and linear discriminant analysis) are used to identify the features. Finally, support vector machine (SVM) is applied to classify the tumor samples of gene expression data based on the identified features. Experiments on seven data sets demonstrate that our methods are effective and feasible for tumor classification.

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e digital image correlation method (DICM) has been applied to similar material simulation experiments for rock-like materials, to overcome the weakness of traditional measurements, for example, data discontinuous. In this paper, the movement and fracturing process of the overlying strata during excavation are observed and studied, and the distributions of stress, strain, and deformation in the overlying strata are obtained based on similar material simulation. e DICM is applied to improve the testing method and to optimize the discontinuity of testing points; of course, the difference of rock deformation in the overlying strata during excavation is considered. Full-field deformation and strain are analyzed by the DICM. To verify the accuracy of the DICM, results obtained from the DICM, numerical simulation and similar material simulation, are compared. e DICM can reflect the characteristics of locality and randomness of rock-like materials more real than numerical simulation, and comparing with similar material simulation, it can directly reproduce the movement and fracturing process of the overlying strata during full-field excavation. It shows that, the DICM is entirely feasible to using in the large scale full-field deformation measurement on complex rock structure, and it is of theoretical importance for testing for rock-like materials.