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Table 8 Performance evaluation for the training set

From: Detection and prevention of SQLI attacks and developing compressive framework using machine learning and hybrid techniques

No

Techniques

Evaluation Metrics

Precision

Recall

F1-score

Training set accuracy

Training time (in sec.)

 

NB

88.33%

87.89%

88.11%

89.40%

08.73

 

DT

93.09%

92.75%

92.92%

95.70%

53.01

 

SVM

97.15%

98.02%

97.58%

98.80%

19.06

 

RF

97.28%

96.00%

96.64%

95.30%

09.48

 

ANN

99.05%

99.65%

99.35%

99.20%

19.62

 

Hybrid

99.54%

99.61%

99.57%

99.60%

26.15