Credit Card Attrition Classification Through Neuronets
Table 1: Performance comparison between all classifiers
| Model |
PS-WASD |
KNB |
Linear SVM |
Fine KNN |
B-WASD |
| MAE |
0.052923 |
0.14652 |
0.092022 |
0.15008 |
0.19155 |
| TP |
0.98603 |
1 |
0.96648 |
0.92551 |
0.79562 |
| FP |
0.013966 |
0 |
0.03352 |
0.074488 |
0.20438 |
| TN |
0.72917 |
0.033854 |
0.58073 |
0.42708 |
0.88021 |
| FN |
0.27083 |
0.96615 |
0.41927 |
0.57292 |
0.11979 |
| Precision |
0.98603 |
1 |
0.96648 |
0.92551 |
0.79562 |
| Recall |
0.78452 |
0.50861 |
0.69744 |
0.61766 |
0.86914 |
| Accuracy |
0.94708 |
0.85348 |
0.90798 |
0.84992 |
0.80845 |
| F_measure |
0.87381 |
0.67428 |
0.81021 |
0.74088 |
0.83076 |
< Back to article
