Wang Ning1,*, Siliang Chen2,*, Fu Qiang2, Haitao Tang2, Shen Jie2
CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5951-5965, 2023, DOI:10.32604/cmc.2023.035558
Abstract With the popularity of online payment, how to perform credit card fraud detection more accurately has also become a hot issue. And with the emergence of the adaptive boosting algorithm (Adaboost), credit card fraud detection has started to use this method in large numbers, but the traditional Adaboost is prone to overfitting in the presence of noisy samples. Therefore, in order to alleviate this phenomenon, this paper proposes a new idea: using the number of consecutive sample misclassifications to determine the noisy samples, while constructing a penalty factor to reconstruct the sample weight assignment. Firstly, the theoretical analysis shows that… More >
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