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Table 3 The performance of models developed on EGFR10 dataset, class-specific molecules and EGFR10 excluding single class, evaluated using cross-validation techniques for testing on same-class of molecules

From: QSAR based model for discriminating EGFR inhibitors and non-inhibitors using Random forest

Trained on

Tested on

Sensitivity

Specificity

Accuracy

MCC

ROC

EGFR10 train

EGFR10 train

68.74

87.67

84.95

0.49

0.89

EGFR10 train

EGFR10 Validation

69.89

86.03

83.66

0.49

0.89

Pyrimidine

Pyrimidine

69.25

92.13

86.92

0.62

0.92

Pyrimidine

Quinazoline

68.62

54.88

58.88

0.21

0.67

Quinazoline

Quinazoline

68.15

79.63

76.31

0.45

0.81

Quinazoline

Pyrimidine

67.86

64.04

64.91

0.27

0.74

EFGR10-Pyrimidine

EFGR10-Pyrimidine

68.7

94.08

91.34

0.59

0.92

EFGR10-Quinazoline

EFGR10- Quinazoline

69.66

96.4

94.04

0.64

0.95

EFGR10- Pyrimidine

Pyrimidine

68.06

76.74

74.77

0.4

0.77

EFGR10- Quinazoline

Quinazoline

60.31

76.25

71.66

0.35

0.72