Fraud Detection Using Support Vector Machine Ensemble

摘要：

As a general fraud detection method in customer resource management (CRM) user profiling can eventually be induced to binary classification and multi-classification problems of support vector machine (SVM). In this paper, we propose the SVM ensemble, in which similar SVMs are employed to detect a specific pattern of customer fraudulent behavior, and majority strategy are used to issut fraud alarm. Compared with other machine learning models, such as MLP and SOM models, either the classification accuracy or the adaptability of the SVM ensemble is remarkable. Our application simulation shows that fur design has better performance than our previously developed system.

关键词： Support vector machine Fraud detection User profiling Binary classification CRM

作者: S.N. Pang Daijin Kim S.Y. Bang

作者单位: Dept. or Computer Science & Engineering, POSTECH San 31 Hyoja-dong, Pohang, 790-784, Korea

会议类型: 国际会议

会议名称: 8th International Conference on Neural Information Processing(ICONIP 2001)(第八届国际神经信息处理大会)

会议地点: 上海

会议语种:英文

页码: 1382-1387

在线出版日期: 2001-11-14（万方平台首次上网日期，不代表论文的发表时间）