VAMPr: VAriant Mapping and Prediction of antibiotic resistance via explainable features and machine learning
Among 93 prediction models, we listed the top 32 models that have the mean prediction accuracies higher than 95%. The isolate and variant counts derived from sequencing were used to build the prediction model using gradient boosting tree algorithms. The accuracy is reported using nested cross validation approach. The 10-fold outer cross validation were used to report accuracy and the 5-fold inner cross validation was used for hyperparameter tuning.