Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights
Fig 5
Cross-stage analysis of disease discrimination in the cirrhosis dataset, which was generated in two independent stages (discovery and validation).
The “All” columns and rows show results when all samples are combined. When the training (TR) and test (TS) stages coincide, the analysis was done in cross-validation (with the margin of error reported in parenthesis). In the other cases, the model was generated on TR and then applied to TS. In bold we report the best value for each scenario and feature type (i.e., species abundance or marker presence), and circled are the overall best value for each scenario.