- This algorithm consolidates 11 underlying Random Forest models. These models were chosen based on their efficacy (ROC-AUC >= 0.9 from 10 randomly seeded trials) from a comprehensive array of models that can be generated by 10 peptides (1024 models).
- The Final Prediction is determined by the Majority vote (Hard voting).
- Certainty indicates the percentage of agreement among the underlying models regarding the Final Prediction.