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ResearchFormerly WizWand

Credit Card Fraud Detection on BankSim (Precision@K)

97.6Precision@KRF
52.77664.41376.0587.687Aug 31, 2025
Updated 5mo ago

Evaluation results

MethodLinks
RFK=0.1, N_l=129732025.0897.6
FNK=0.1, N_l=259462025.0897.6
FNK=0.1, N_l=129732025.0896.9
RFK=0.2, N_l=259462025.0896.4
RFK=0.1, N_l=38932025.0896.2
FNK=0.1, N_l=51902025.0896.2
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.1, N_l=129732025.0896.2
RFK=0.1, N_l=259462025.0896.2
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.1, N_l=259462025.0896.2
FNK=0.2, N_l=129732025.0895.9
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.2, N_l=259462025.0895.9
FNK=0.5, N_l=259462025.0895.8
FNK=0.2, N_l=259462025.0895.7
FNK=0.1, N_l=38932025.0895.5
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.2, N_l=38932025.0895.3
FNK=0.2, N_l=51902025.0895.3
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.2, N_l=129732025.0895.3
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.2, N_l=51902025.0895.2
RFK=0.2, N_l=129732025.0895.2
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.5, N_l=259462025.0895.2
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.1, N_l=25952025.0894.8
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.1, N_l=38932025.0894.8
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.1, N_l=51902025.0894.8
SVMK=0.2, N_l=259462025.0894.5
FNK=0.5, N_l=129732025.0894.5
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.5, N_l=129732025.0894.4
RFK=0.1, N_l=51902025.0894.1
FNK=0.2, N_l=38932025.0893.8
RFK=0.5, N_l=259462025.0893.8
RFK=0.2, N_l=51902025.0893.6
RFK=0.1, N_l=25952025.0893.4
RFK=0.2, N_l=38932025.0893.3
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.2, N_l=25952025.0892.9
SVMK=0.1, N_l=259462025.0892.8
FNK=0.1, N_l=25952025.0892.4
SVMK=0.2, N_l=129732025.0892.1
RFK=0.5, N_l=129732025.0892
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.5, N_l=51902025.0891.9
RFK=0.2, N_l=25952025.0891.2
SVMK=0.1, N_l=129732025.0891
FNK=0.5, N_l=51902025.0891
FNK=0.2, N_l=25952025.0890.7
SVMK=0.5, N_l=259462025.0889.8
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.5, N_l=38932025.0889.6
SVMK=0.5, N_l=129732025.0888.9
SVMK=0.1, N_l=51902025.0888.6
Semi-Supervised Bayesian GANs with Log-SignaturesK=0.5, N_l=25952025.0888.3
RFK=0.5, N_l=51902025.0888
FNK=0.5, N_l=38932025.0887.7
SVMK=0.2, N_l=51902025.0885.2
RFK=0.5, N_l=38932025.0885.2
LK=0.1, N_l=259462025.0883.4
FNK=0.5, N_l=25952025.0883.3
RFK=0.5, N_l=25952025.0881.9
KNNK=0.2, N_l=259462025.0881
SVMK=0.5, N_l=51902025.0880.2
SVMK=0.1, N_l=38932025.0880
KNNK=0.1, N_l=259462025.0880
SVMK=0.2, N_l=38932025.0878.3
LK=0.2, N_l=259462025.0877.9
FNK=1.0, N_l=259462025.0877.9
L-SSLK=0.2, N_l=259462025.0877.8
KNNK=0.1, N_l=129732025.0877.2
L-SSLK=0.1, N_l=259462025.0877.2
Semi-Supervised Bayesian GANs with Log-SignaturesK=1.0, N_l=259462025.0877
RFK=1.0, N_l=259462025.0876.6
Semi-Supervised Bayesian GANs with Log-SignaturesK=1.0, N_l=129732025.0876.4
FNK=1.0, N_l=129732025.0875.6
RFK=1.0, N_l=129732025.0875.1
LK=0.1, N_l=129732025.0874.5
L-SSLK=0.1, N_l=129732025.0874.5
SVMK=0.1, N_l=25952025.0872.1
SVMK=1.0, N_l=259462025.0872.1
Semi-Supervised Bayesian GANs with Log-SignaturesK=1.0, N_l=51902025.0871.5
SVMK=0.5, N_l=38932025.0870.9
L-SSLK=0.1, N_l=51902025.0870.7
RFK=1.0, N_l=51902025.0870.1
L-SSLK=0.2, N_l=129732025.0870
KNNK=0.2, N_l=129732025.0870
FNK=1.0, N_l=51902025.0870
SVMK=1.0, N_l=129732025.0869.8
L-SSLK=0.1, N_l=38932025.0869.3
Semi-Supervised Bayesian GANs with Log-SignaturesK=1.0, N_l=38932025.0868.4
RFK=1.0, N_l=38932025.0868.1
SVMK=0.2, N_l=25952025.0867.9
FNK=1.0, N_l=38932025.0867.7
RFK=1.0, N_l=25952025.0866.9
Semi-Supervised Bayesian GANs with Log-SignaturesK=1.0, N_l=25952025.0865.5
LK=0.2, N_l=129732025.0865.3
FNK=1.0, N_l=25952025.0864.9
SVMK=1.0, N_l=51902025.0863.6
L-SSLK=0.5, N_l=259462025.0862.1
SVMK=0.5, N_l=25952025.0859.4
LK=0.5, N_l=259462025.0858.3
KNNK=0.1, N_l=51902025.0857.9
SVMK=1.0, N_l=38932025.0857.3
L-SSLK=0.2, N_l=51902025.0856
L-SSLK=0.1, N_l=25952025.0855.9
KNNK=0.5, N_l=259462025.0854.9
LK=0.1, N_l=51902025.0854.5