Figure 3.

Lasso feature selection improved ML model performance. We performed SVM for FSGS with no feature selection (842 metabolites) and with a forward feature selection (122 metabolites on the basis of LR P<0.05). All three iterations demonstrated better performance than no-skill selection in 20% holdout validation subsets. The SVM with Lasso feature selection outperformed both no-selection and forward-selection models. There were not significant differences in metabolite subpathway signals detected. 95% CI, 95% confidence interval.