Aiming at the imbalanced overlapping problem of credit card transaction data,an end-to-end one class classification method based on generation countermeasure network was proposed.A method based on PCA and T_SNE hybrid data dimension reduction method was proposed,which reduced the dimension of the cleaned data.The reduced dimension data was sent into the proposed LSTM and aMLP based generation countermeasure network(aLMGAN),and a Minkowski distance based loss func-tion(Min-loss)was proposed to replace the cross entropy loss function in the original generation countermeasure network,and single class stability training was conducted for normal transaction data to form a special feature mode to distinguish abnormal data that did not belong to this feature.By using two real public credit card transaction datasets on kaggle,the experiment veri-fies the effectiveness of aLMGAN algorithm.
维普
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