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Table 1 Performance measures for each model

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

70.27 ± 5.21

70.30 ± 5.92

74.09 ± 6.66

70.72 ± 5.55

0.54 ± 0.11

TAN

71.01 ± 4.19

70.29 ± 5.84

74.21 ± 4.52

70.81 ± 5.39

0.56 ± 0.11

SVM

70.63 ± 4.43

70.31 ± 5.22

73.68 ± 5.26

70.55 ± 5.31

0.55 ± 0.08

DT

69.27 ± 7.19

69.93 ± 5.02

73.16 ± 4.14

70.72 ± 4.82

0.52 ± 0.10

RF

69.07 ± 4.93

67.70 ± 4.78

71.08 ± 7.41

67.30 ± 5.78

0.51 ± 0.07

RVFL

70.11 ± 5.34

70.44 ± 4.31

74.16 ± 4.32

71.19 ± 4.35

0.54 ± 0.11

ATAN

71.10 ± 5.77

70.22 ± 3.56

73.89 ± 4.29

71.36 ± 4.36

0.56 ± 0.09

HC-TAN

70.41 ± 7.44

69.67 ± 6.39

73.95 ± 6.04

70.22 ± 6.26

0.58 ± 0.11

HC-SP-TAN

70.81 ± 6.48

71.63 ± 4.81

74.98 ± 5.98

71.98 ± 5.36

0.56 ± 0.11

BSEJ

71.09 ± 4.24

72.09 ± 5.95

74.28 ± 5.22

71.09 ± 5.11

0.55 ± 0.12

FSSJ

71.69 ± 3.92

72.03 ± 3.34

73.88 ± 5.02

72.27 ± 4.56

0.58 ± 0.09

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

74.09 ± 3.62

73.89 ± 2.54

76.88 ± 2.34

75.14 ± 3.24

0.59 ± 0.08