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Table 2 The results were obtained by applying pre-trained models in combination with five ML classifiers

From: Detecting COVID-19 in chest images based on deep transfer learning and machine learning algorithms

Model

Classifier

Performance metrics (%)

Accuracy

Recall

Precision

F1 score

DenseNet201

RF

99.44

99.44

99.45

99.44

SVM

96.48

96.48

96.50

96.50

DT

93.61

93.61

93.69

93.60

KNN

100

100

100

100

LGR

99.16

99.16

99.17

99.16

ResNet50

RF

98.14

98.14

98.17

98.15

SVM

89.9

89.9

90.29

89.88

DT

92.77

92.77

92.84

92.77

KNN

99.81

99.81

99.81

99.81

LGR

98.24

98.24

98.24

98.24

Xception

RF

94.16

94.16

94.21

94.16

SVM

89.53

89.53

89.68

89.52

DT

85

85

85

84.98

KNN

99.62

99.62

99.63

99.62

LGR

97.59

97.59

97.59

97.59

VGG16

RF

99.07

99.07

99.08

99.08

SVM

90.27

90.27

90.44

90.26

DT

93.14

93.14

93.15

93.14

KNN

99.81

99.81

99.81

99.81

LGR

95.55

95.55

95.57

95.55