JFRM  Vol.6 No.2 , June 2017
The P2P Risk Assessment Model Based on the Improved AdaBoost-SVM Algorithm
Abstract: The improved AdaBoost-SVM algorithm is used to classify the safety and the risk from the Peers-to-Peers net loan platforms. Since the SVM algorithm is hard to deal with the rare samples and its training is slow, rule sampling is used to reduce the classify noise. Then, with the combinations of learning machine, P2P risks can be identified. The result shows that IAdaBoost algorithm can improve the risk platform classification accuracy. And the error of classification can be controlled in 5%.
Cite this paper: Yang, J. and Luo, D. (2017) The P2P Risk Assessment Model Based on the Improved AdaBoost-SVM Algorithm. Journal of Financial Risk Management, 6, 201-209. doi: 10.4236/jfrm.2017.62015.

[1]   Chew, H.-G., Crisp, D. J., Bogner, R. E. et al. (2000). Target Detection in Radar Imagery Using Support Vector Machines with Training Size Biasing. In Proceedings of the Sixth International Conference on Control, Automation, Robotics and Vision, Singapore.

[2]   Dong, L. H., Geng, G. H., & Zhou, M. Q. (2007). Design of Text Automatic Classifier Based on Boosting Algorithm. Computer Applications, No. 2, 384-386.

[3]   Joshi, M. V., Agarwal, R. C., & Kumar, V. (2002). Predict Rare Classes: Can Boosting Make Any Weak Learner Strong? In Proceedings of the Eighth ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2002), Edmonton, Canada.

[4]   Ju, X., Wang, H., & Yao, H. L. (2012). Combinatorial Classifier Based on Boosting Support Vector Machine. Journal of Hefei University of Technology, No. 10, 1220-1222.

[5]   Li, Y. J., Liu, X. X., & Chen, P. (2015). Improved AdaBoost Algorithm and SVM Combinatorial Classifier. Computer Engineering and Applications, 44-32.

[6]   Liu, Z. T. (2013). China’s P2P Network Credit Risk Assessment. Nanning: Guangxi University.

[7]   Luo, C. Y. (2012). P2P Network Lending in the Investment Decision Model. Dalian: Dalian University of Technology.

[8]   Tan, P.-N., Steinbach, M., & Kumar, V. (2006). Introduction to Data Raining Is 1: Posts & Telecom Pushers Inc.

[9]   Wang, F. (2016). China’s P2P Network Lending Platform Risk Regulation and Prevention. China Circulation Economy, 121-127.

[10]   Wang, Y. Z., & Le, S. B. (2005). Multiboot-Based Minimum Classification Error Algorithm. Small Microcomputers, No. 11, 1948-1950.

[11]   Ye, Q., Li, Z. Q., & Xu, W. H. (2016). Study on Risk Identification of P2P Network Borrowing Platform. Accounting Research, 38-45.

[12]   Yu, J. M. (2015). Network Lending (P2P) Platform Quantitative Monitoring Research. Guangzhou: South China University of Technology.