Table 3 Test accuracies for HIV classification utilizing ten ML models.

From: Scalable and robust machine learning framework for HIV classification using clinical and laboratory data

ML models

With 22 features

With 12 selected features

RFC

86.16%

86.49%

DTC

80.14%

79.97%

LR

65.05%

62.97%

AB

66%

64%

KNN

66%

66%

GB

60.57%

60.63%

LightGBM

60.50%

60.41%

XGBoost

59.19%

59.24%

MLP

62.98%

64.60%

NB

61.36%

64.58%

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