E-commerce fraud risk prediction based on RUSBoost algorithm
International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021)(2022)
Abstract
In the context of the era of big data, the emergence of e-commerce platforms has brought many opportunities and risks. Due to the COVID-19, e-commerce has achieved unprecedented development, and e-commerce fraud has severely damaged the healthy economic environment. This paper uses the RUSBoost algorithm to build an e-commerce fraud risk prediction model, and verifies the predictive performance of the model through data experiments. The results show that it has a high accuracy rate for identifying e-commerce fraud. If the model is applied to e-commerce, the losses caused by ecommerce fraud could be avoided in time. At present, there are fewer e-commerce fraud risk prediction models and have a wide development prospection.
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Key words
rusboost algorithm,prediction,e-commerce
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