Figure 4

The overview of biomarker genera mining using GA. From the randomly generated initial 300 individuals consisting of genera, the classification model was optimized using GA methods, including crossover and mutation. The model with the highest fitness score is selected for each generation and further sequentially optimized in the next generation. The final model was evaluated using the average AUROC of the tenfold CV model. Further model validation was conducted using test data for the corresponding biomarker subset and accuracy, an F1-score, a kappa, and an AUROC.