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Table 4 Performance of the machine-learning algorithms

From: Machine-learning based prediction of prognostic risk factors in patients with invasive candidiasis infection and bacterial bloodstream infection: a singled centered retrospective study

Model

Accuracy

Precision

Recall

F1

AUC

Logistic regression (LR)

0.716

0.559

0.760

0.644

0.753

Random forest (RF)

0.784

0.622

0.920

0.742

0.919

Support vector machine (SVM)

0.622

0.465

0.800

0.588

0.777