Article | Classification Technique | Results | |||||||||||
Accuracy | TT (sec) | prediction | TP | TN | FP | FN | Error rate | Precision | Recall | DR | FAR | ||
4: Frature Classification and outlier detection to increased accuracy in intrusion detection system. | C45 | 99.94% | 199.33 before 23.14 after | . | . | . | . | . | . | . | . | . | . |
KNN | 99.90% | 0.37 before 0.23 After | . | . | . | . | . | . | . | . | . | . | |
Naïve bayes | 96.16% | 5.63 before 1.36 after | . | . | . | . | . | . | . | . | . | . | |
Random forest | 99.94% | 554.63 before 205.97 after | . | . | . | . | . | . | . | . | . | . | |
SVM | 99.94% | 699.07 before 186.53 after | . | . | . | . | . | . | . | . | . | . |