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Credit Card Fraud Detection Using RUS and MRN Algorithms

机译:使用RUS和MRN算法的信用卡欺诈检测

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Currently, enterprise systems have been focusing on expenditure services through credit card broadly because it is convenient and quick to pay for products and services. Thus, this research emphasizes on the fraud detection of credit card payment by using the machine learning technique called RUSMRN. The proposed method adopts three base classifiers which are MLP, NB and Naive Bayes algorithms. In addition, it can analyze the correctness to work with the unbalance datasets. Therefore, this research is focusing on the information of the credit card company of Taiwan for collecting data of customer behaviors in credit card payment. After that, it has brought the information to make prediction for correctness whether it has the risks in payment. The result shows that the proposed method can achieve the best classification performance in terms of accuracy and sensitivity.
机译:目前,企业系统一直专注于通过信用卡广泛关注支出服务,因为它方便快捷地支付产品和服务。因此,通过使用称为Rusmrn的机器学习技术强调了欺诈性检测信用卡付款。所提出的方法采用三个基础分类器,其是MLP,NB和NAIVE Bayes算法。此外,它可以分析与不平衡数据集一起使用的正确性。因此,本研究专注于台湾信用卡公司的信息,用于收集信用卡付款中的客户行为数据。之后,它使信息能够对正确性进行预测,无论是否有付款风险。结果表明,所提出的方法可以在准确性和灵敏度方面实现最佳分类性能。

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