Solve fraud detection problem by using graph based learning methods [article]

Loc Tran, Tuan Tran, Linh Tran, An Mai
2019 arXiv   pre-print
The credit cards' fraud transactions detection is the important problem in machine learning field. To detect the credit cards's fraud transactions help reduce the significant loss of the credit cards' holders and the banks. To detect the credit cards' fraud transactions, data scientists normally employ the unsupervised learning techniques and supervised learning techniques. In this paper, we employ the graph p-Laplacian based semi-supervised learning methods combined with the undersampling
more » ... iques such as Cluster Centroids to solve the credit cards' fraud transactions detection problem. Experimental results show that the graph p-Laplacian semi-supervised learning methods outperform the current state of the art graph Laplacian based semi-supervised learning method (p=2).
arXiv:1908.11708v1 fatcat:ptds4r6ehfae5ljaoonp43ow6u