Table 9 Comparison with existing methods
From: A machine learning based credit card fraud detection using the GA algorithm for feature selection
Model | Accuracy |
|---|---|
LR [13] | 97.70 % |
DT [13] | 95.50 % |
SVM [13] | 97.50 % |
NB [14] | 99.23 % |
KNN [16] | 97.69 % |
LR [16] | 54.86 % |
DT [4] | 97.08 % |
LR [17] | 97.18 % |
IF [16] | 58.83 % |
GA-ANN [17] | 81.82 % |
GA-DT [17] | 81.97 % |
GA-RF [17] | 77.95 % |
GA-RF (Proposed \(v_5\)) | 99.98 % |
GA-DT (Proposed \(v_1\)) | 99.92 % |
GA-LR (Proposed \(v_1\)) | 99.91 % |
GA-NB (Proposed \(v_5\)) | 99.44 % |