Table 2 Classifier outcome of MGODEL-ID method under various epochs.

From: Advanced mathematical modeling of mitigating security threats in smart grids through deep ensemble model

Classes

\(\:Acc{u}_{y}\)

Precn

\(\:Rec{a}_{l}\)

\(\:{F1}_{Score}\)

\(\:{G}_{Measure}\)

Epoch − 500

Benign

97.88

98.53

97.88

98.21

98.21

DDoS

97.86

96.92

97.86

97.39

97.39

Average

97.87

97.73

97.87

97.80

97.80

Epoch − 1000

Benign

98.05

98.65

98.05

98.35

98.35

DDoS

98.03

97.16

98.03

97.60

97.60

Average

98.04

97.91

98.04

97.97

97.97

Epoch − 1500

Benign

98.16

98.68

98.16

98.42

98.42

DDoS

98.07

97.32

98.07

97.70

97.70

Average

98.12

98.00

98.12

98.06

98.06

Epoch − 2000

Benign

98.33

98.79

98.33

98.56

98.56

DDoS

98.23

97.57

98.23

97.90

97.90

Average

98.28

98.18

98.28

98.23

98.23

Epoch − 2500

Benign

98.38

98.80

98.38

98.59

98.59

DDoS

98.24

97.64

98.24

97.94

97.94

Average

98.31

98.22

98.31

98.26

98.26

Epoch − 3000

Benign

98.46

98.74

98.46

98.60

98.60

DDoS

98.16

97.75

98.16

97.95

97.95

Average

98.31

98.25

98.31

98.28

98.28