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Random Forest feature selection. Iterative bisection of the number of metabolites by removing the 50% of metabolites with the smallest importance measure. The remaining metabolites were used to build the Random Forest regression model. Shown is the median cross-validation accuracy. The accuracy remains stable up to a pattern of nine metabolites.
