Table 22 Cross-validation result for ML models
From: Apply machine learning techniques to detect malicious network traffic in cloud computing
ML model | K-folds | Accuracy (%) |
|---|---|---|
ANN | 5 | 92 |
ANN | 10 | 94 |
ANN | 15 | 92 |
KNN | 5 | 100 |
KNN | 10 | 100 |
KNN | 15 | 100 |
DTREE | 5 | 100 |
DTREE | 10 | 100 |
DTREE | 15 | 100 |
SVM | 5 | 68 |
SVM | 10 | 81 |
SVM | 15 | 84 |
Naïve Bayes | 5 | 60 |
Naïve Bayes | 10 | 60 |
Naïve Bayes | 15 | 60 |
Random Forest | 5 | 100 |
Random Forest | 10 | 100 |
Random Forest | 15 | 100 |