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Credit Card Fraud Detection Using Random Forest Algorithm

机译:使用随机林算法的信用卡欺诈检测

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In this paper we mainly focus on credit card fraud detection in real world. Here the credit card fraud detection is based on fraudulent transactions. Generally credit card fraud activities can happen in both online and offline. But in today's world online fraud transaction activities are increasing day by day. So in order to find the online fraud transactions various methods have been used in existing system. In proposed system we use Random Forest Algorithm(RFA) for finding the fraudulent transactions and the accuracy of those transactions. This algorithm is based on supervised learning algorithm where it uses decision trees for classification of the dataset. After classification of dataset a confusion matrix is obtained. The performance of Random Forest Algorithm is evaluated based on the confusion matrix. The results obtained from processing the dataset gives accuracy of about 90%.
机译:在本文中,我们主要关注现实世界中的信用卡欺诈检测。这里的信用卡欺诈检测是基于欺诈性交易。通常,信用卡欺诈活动可以在线和离线发生。但在今天的世界在线欺诈交易活动日益日益增加。因此,为了找到在线欺诈事务,在现有系统中使用了各种方法。在提出的系统中,我们使用随机林算法(RFA)来查找欺诈性交易和这些交易的准确性。该算法基于监督学习算法,它使用决策树进行分类数据集。在数据集分类之后,获得了混淆矩阵。基于混淆矩阵评估随机林算法的性能。从处理数据集获得的结果可以精确为约90%。

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