Open Journal of Social Sciences

Volume 2, Issue 4 (April 2014)

ISSN Print: 2327-5952   ISSN Online: 2327-5960

Google-based Impact Factor: 0.93  Citations  

Integrated Learning-Based SME Credit Rating

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DOI: 10.4236/jss.2014.24036    4,621 Downloads   5,921 Views   Citations


SME Credit rating index system becomes a significant research topic in recent years. So many researches have focused on this topic. However, the existing researches are only focused on one aspect of the SME Credit Rating problem. In order to resolve this problem, in this paper, we use the idea of ensemble learning, which integrated several basic machine learning algorithms to improve the learning result. Through further amendments, we build a set of SME corporate credit evaluation models which have higher forecast accuracy and stronger anti-jamming capability. Finally, we prove the effectiveness of our model through carrying out a set of experiments.

Cite this paper

Wang, L. , Wang, Z. , Hu, Y. and Bai, T. (2014) Integrated Learning-Based SME Credit Rating. Open Journal of Social Sciences, 2, 326-333. doi: 10.4236/jss.2014.24036.

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