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Variable (wavelength or feature) selection techniques have become a critical step for the analysis of datasets with high number of variables and relatively few samples. In this study, a novel variable selection strategy, variable combination population analysis (VCPA), was proposed. This strategy consists of two crucial procedures. First, the exponentially(More)
Main target of metabolomics research is to reveal informative metabolites or biomarkers, which can be considered as a process of variable selection. So far, several methods, such as regression coefficient (RC), weights or variable importance in projection (VIP), have been widely used to assess the variable importance when building the partial least squares(More)
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