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Table 3 Performance measures for each model (with four attributes)

From: Facial biotype classification for orthodontic treatment planning using an alternative learning algorithm for tree augmented Naive Bayes

Algorithm

Accuracy

Precision

Recall

\(F_{1}\)-score

Kappa

 

Avg. ± SD.

Avg. ± SD.

Avg. ± SD.

Avg. ± SD.

Avg. ± SD.

NB

72.27 ± 5.03

72.36 ± 5.63

76.23 ± 5.61

72.84 ± 5.81

0.57 ± 0.09

TAN

72.18 ± 3.53

72.41 ± 6.66

76.43 ± 6.16

73.33 ± 6.95

0.56 ± 0.05

SVM

66.90 ± 4.59

67.86 ± 4.91

71.89 ± 6.22

69.23 ± 6.73

0.49 ± 0.07

DT

69.63 ± 5.21

69.63 ± 3.27

72.79 ± 2.74

70.04 ± 3.18

0.52 ± 0.08

RF

70.27 ± 4.06

71.28 ± 4.45

73.82 ± 4.24

71.11 ± 4.46

0.54 ± 0.06

RVFL

71.53 ± 5.67

72.51 ± 4.56

76.56 ± 6.21

73.11 ± 5.55

0.56 ± 0.09

ATAN

72.21 ± 4.78

72.25 ± 4.96

76.43 ± 6.78

73.01 ± 5.99

0.58 ± 0.09

HC-TAN

72.12 ± 5.01

72.07 ± 5.73

75.33 ± 3.71

72.73 ± 5.11

0.58 ± 0.10

HC-SP-TAN

71.09 ± 7.03

71.82 ± 5.34

74.27 ± 5.01

72.11 ± 5.28

0.55 ± 0.09

BSEJ

71.63 ± 6.03

71.76 ± 4.65

74.80 ± 5.12

72.26 ± 4.51

0.56 ± 0.09

FSSJ

72.27 ± 4.43

72.35 ± 4.75

76.20 ± 6.86

72.81 ± 6.26

0.58 ± 0.09

\((\mu ,\lambda )\)-TAN

75.05 ± 3.86

74.85 ± 4.58

77.85 ± 4.46

75.51 ± 6.36

0.60 ± 0.07