Table 2 Model efficiency assessment: evaluation metric scores.

From: A comprehensive machine learning for high throughput Tuberculosis sequence analysis, functional annotation, and visualization

ML models

Accuracy

Log loss

Precision

Recall

RocAuc

Specificity

F1-score

TPR

FPR

XG boost

0.963

0.139

0.95

0.964

0.985

0.962

0.957

0.964

0.038

Logistic regression

0.739

0.553

0.737

0.609

0.193

0.837

0.667

0.609

0.163

Random forest

0.773

0.555

0.815

0.609

0.099

0.897

0.697

0.609

0.103

AdaBoost

0.866

0.666

0.847

0.840

0.060

0.886

0.844

0.840

0.114

SupportVector machine

0.866

0.661

0.874

0.804

0.115

0.913

0.838

0.804

0.087

Back to article page