Credit Card Fraud Detection on BankSim (Precision@K)
97.6Precision@KRF
Evaluation Results
| Method | Links | |
|---|---|---|
| RFK=0.1, N_l=129732025.08 | 97.6 | |
| FNK=0.1, N_l=259462025.08 | 97.6 | |
| FNK=0.1, N_l=129732025.08 | 96.9 | |
| RFK=0.2, N_l=259462025.08 | 96.4 | |
| RFK=0.1, N_l=38932025.08 | 96.2 | |
| FNK=0.1, N_l=51902025.08 | 96.2 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.1, N_l=129732025.08 | 96.2 | |
| RFK=0.1, N_l=259462025.08 | 96.2 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.1, N_l=259462025.08 | 96.2 | |
| FNK=0.2, N_l=129732025.08 | 95.9 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.2, N_l=259462025.08 | 95.9 | |
| FNK=0.5, N_l=259462025.08 | 95.8 | |
| FNK=0.2, N_l=259462025.08 | 95.7 | |
| FNK=0.1, N_l=38932025.08 | 95.5 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.2, N_l=38932025.08 | 95.3 | |
| FNK=0.2, N_l=51902025.08 | 95.3 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.2, N_l=129732025.08 | 95.3 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.2, N_l=51902025.08 | 95.2 | |
| RFK=0.2, N_l=129732025.08 | 95.2 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.5, N_l=259462025.08 | 95.2 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.1, N_l=25952025.08 | 94.8 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.1, N_l=38932025.08 | 94.8 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.1, N_l=51902025.08 | 94.8 | |
| SVMK=0.2, N_l=259462025.08 | 94.5 | |
| FNK=0.5, N_l=129732025.08 | 94.5 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.5, N_l=129732025.08 | 94.4 | |
| RFK=0.1, N_l=51902025.08 | 94.1 | |
| FNK=0.2, N_l=38932025.08 | 93.8 | |
| RFK=0.5, N_l=259462025.08 | 93.8 | |
| RFK=0.2, N_l=51902025.08 | 93.6 | |
| RFK=0.1, N_l=25952025.08 | 93.4 | |
| RFK=0.2, N_l=38932025.08 | 93.3 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.2, N_l=25952025.08 | 92.9 | |
| SVMK=0.1, N_l=259462025.08 | 92.8 | |
| FNK=0.1, N_l=25952025.08 | 92.4 | |
| SVMK=0.2, N_l=129732025.08 | 92.1 | |
| RFK=0.5, N_l=129732025.08 | 92 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.5, N_l=51902025.08 | 91.9 | |
| RFK=0.2, N_l=25952025.08 | 91.2 | |
| SVMK=0.1, N_l=129732025.08 | 91 | |
| FNK=0.5, N_l=51902025.08 | 91 | |
| FNK=0.2, N_l=25952025.08 | 90.7 | |
| SVMK=0.5, N_l=259462025.08 | 89.8 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.5, N_l=38932025.08 | 89.6 | |
| SVMK=0.5, N_l=129732025.08 | 88.9 | |
| SVMK=0.1, N_l=51902025.08 | 88.6 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=0.5, N_l=25952025.08 | 88.3 | |
| RFK=0.5, N_l=51902025.08 | 88 | |
| FNK=0.5, N_l=38932025.08 | 87.7 | |
| SVMK=0.2, N_l=51902025.08 | 85.2 | |
| RFK=0.5, N_l=38932025.08 | 85.2 | |
| LK=0.1, N_l=259462025.08 | 83.4 | |
| FNK=0.5, N_l=25952025.08 | 83.3 | |
| RFK=0.5, N_l=25952025.08 | 81.9 | |
| KNNK=0.2, N_l=259462025.08 | 81 | |
| SVMK=0.5, N_l=51902025.08 | 80.2 | |
| SVMK=0.1, N_l=38932025.08 | 80 | |
| KNNK=0.1, N_l=259462025.08 | 80 | |
| SVMK=0.2, N_l=38932025.08 | 78.3 | |
| LK=0.2, N_l=259462025.08 | 77.9 | |
| FNK=1.0, N_l=259462025.08 | 77.9 | |
| L-SSLK=0.2, N_l=259462025.08 | 77.8 | |
| KNNK=0.1, N_l=129732025.08 | 77.2 | |
| L-SSLK=0.1, N_l=259462025.08 | 77.2 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=1.0, N_l=259462025.08 | 77 | |
| RFK=1.0, N_l=259462025.08 | 76.6 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=1.0, N_l=129732025.08 | 76.4 | |
| FNK=1.0, N_l=129732025.08 | 75.6 | |
| RFK=1.0, N_l=129732025.08 | 75.1 | |
| LK=0.1, N_l=129732025.08 | 74.5 | |
| L-SSLK=0.1, N_l=129732025.08 | 74.5 | |
| SVMK=0.1, N_l=25952025.08 | 72.1 | |
| SVMK=1.0, N_l=259462025.08 | 72.1 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=1.0, N_l=51902025.08 | 71.5 | |
| SVMK=0.5, N_l=38932025.08 | 70.9 | |
| L-SSLK=0.1, N_l=51902025.08 | 70.7 | |
| RFK=1.0, N_l=51902025.08 | 70.1 | |
| L-SSLK=0.2, N_l=129732025.08 | 70 | |
| KNNK=0.2, N_l=129732025.08 | 70 | |
| FNK=1.0, N_l=51902025.08 | 70 | |
| SVMK=1.0, N_l=129732025.08 | 69.8 | |
| L-SSLK=0.1, N_l=38932025.08 | 69.3 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=1.0, N_l=38932025.08 | 68.4 | |
| RFK=1.0, N_l=38932025.08 | 68.1 | |
| SVMK=0.2, N_l=25952025.08 | 67.9 | |
| FNK=1.0, N_l=38932025.08 | 67.7 | |
| RFK=1.0, N_l=25952025.08 | 66.9 | |
| Semi-Supervised Bayesian GANs with Log-SignaturesK=1.0, N_l=25952025.08 | 65.5 | |
| LK=0.2, N_l=129732025.08 | 65.3 | |
| FNK=1.0, N_l=25952025.08 | 64.9 | |
| SVMK=1.0, N_l=51902025.08 | 63.6 | |
| L-SSLK=0.5, N_l=259462025.08 | 62.1 | |
| SVMK=0.5, N_l=25952025.08 | 59.4 | |
| LK=0.5, N_l=259462025.08 | 58.3 | |
| KNNK=0.1, N_l=51902025.08 | 57.9 | |
| SVMK=1.0, N_l=38932025.08 | 57.3 | |
| L-SSLK=0.2, N_l=51902025.08 | 56 | |
| L-SSLK=0.1, N_l=25952025.08 | 55.9 | |
| KNNK=0.5, N_l=259462025.08 | 54.9 | |
| LK=0.1, N_l=51902025.08 | 54.5 |