Table 9 Average performance comparison with state-of-art methods.

From: Enhancing education quality with hybrid clustering and evolutionary neural networks in a multi phase framework

Methods

Accuracy

Precision

Recall

Specificity

F-score

Error rate

Time taken (S)

K-NN

0.70

0.71

0.68

0.72

0.70

0.30

49

NN

0.88

0.87

0.89

0.86

0.88

0.12

72

SVM

0.71

0.73

0.66

0.75

0.69

0.28

57

DT

0.72

0.74

0.68

0.76

0.71

0.27

32

NB

0.74

0.76

0.70

0.78

0.73

0.27

19

DT-SVM

0.82

0.84

0.79

0.85

0.81

0.19

90

NB-KNN

0.76

0.79

0.73

0.80

0.75

0.24

199

DT-SVM-KNN

0.79

0.81

0.75

0.82

0.78

0.21

119

NB-NN-DT

0.87

0.89

0.85

0.89

0.87

0.14

45

SVM-NB-KNN

0.84

0.86

0.82

0.87

0.83

0.15

70

NeuroEvoClass

0.92

0.91

0.89

0.91

0.90

0.09

75