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Table 1 Performance of COVID-19 classification achieved by SVM, KNN, LR, GaussianNB, QDA, RF, HAFS-RF (\(\alpha =0.5\))

From: Pulmonary lesion subtypes recognition of COVID-19 from radiomics data with three-dimensional texture characterization in computed tomography images

Method Label Precision (%) Recall (%) Accuracy (%) F-measure (%)
SVM 1 76.34 99.42 82.3 86.37
2 99.48 62.07 92.31% 76.45
3 100.0 57.75 98.04 73.21
4 96.84 58.2 91.75 72.71
KNN 1 88.04 86.32 85.66 87.17
2 83.09 83.23 93.19 83.16
3 78.05 86.49 98.17 82.05
4 65.98 67.96 87.58 66.96
LR 1 83.46 88.4 83.8 85.86
2 76.93 75.3 89.83 76.11
3 66.67 52.11 96.58 58.5
4 55.86 50.27 83.7 52.92
GaussianNB 1 88.57 59.6 72.88 71.25
2 42.62 62.72 75.52 50.75
3 14.64 86.62 76.01 25.05
4 37.82 10.19 79.89 16.05
QDA 1 95.14 36.67 63.72 52.94
2 39.1 97.27 66.82 55.78
3 100.0 99.3 99.97 99.65
4 43.38 48.66 79.07 45.87
DT 1 91.85 92.57 91.49 92.21
2 91.53 87.21 95.53 89.32
3 86.75 90.34 98.89 88.51
4 78.36 79.93 91.79 79.14
RF 1 89.70 93.31 90.42 91.47
2 84.92 83.59 93.48 84.25
3 86.11 87.94 98.79 87.02
4 80.78 72.53 91.30 76.43
HAFS-RF (our) 1 92.21 95.52 93.06 93.84
2 93.17 91.58 96.84 92.37
3 95.14 95.8 99.58 95.47
4 88.43 80.75 94.3 84.42
  1. Bold values indicate the maximum value of each type of lesion classification index