tailieunhanh - Variable selection for binary classification using error rate p-values applied to metabolomics data

Metabolomics datasets are often high-dimensional though only a limited number of variables are expected to be informative given a specific research question. The important task of selecting informative variables can therefore become complex. In this paper we look at discriminating between two groups. |

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