Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights
Fig 3
Prediction performances (assessed using AUC) for disease discrimination in different cross-validation studies.
Species abundance and marker presence are the microbiome features used by the classifiers. The best value for each dataset and feature type (i.e., species abundance or marker presence) are in bold, and the overall best values for each dataset are circled. RF and SVM are applied on the entire set of features whereas RF-FS:Emb incorporates a feature selection step (see Methods). Margins of error are reported in parenthesis.