Fig_2.tif (500.77 kB)

Identification accuracies of the five methods on simulation data with different parameters, where p_S is taken as the parameter in the case of PRFE p_L = 1 to test the performance of different p_S values; p_L is taken as the parameter in the case of PRFE p_S = 1 to test the performance of different p_L values; α₁, α₂ and γ are the control-sparsity parameters of PMD, CIPMD and SPCA, respectively.

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posted on 2015-07-22, 03:29 authored by Jian Liu, Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong, Xue-Song Wang, Dong Wang

Identification accuracies of the five methods on simulation data with different parameters, where p_S is taken as the parameter in the case of PRFE p_L = 1 to test the performance of different p_S values; p_L is taken as the parameter in the case of PRFE p_S = 1 to test the performance of different p_L values; α₁, α₂ and γ are the control-sparsity parameters of PMD, CIPMD and SPCA, respectively.

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Biological Sciences

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identification accuracies regularization function feature extraction method error function Numerous experiments gene expression data gene expression data sets simulation data show differentially

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