Credit Rating Prediction by Using Machine Learning Methods

credit rating;machine learning;logistic regression;neural networks;support vector machine;510

자연과학대학 수리과학부 ;

University:서울대학교 대학원

关键词: credit rating;    machine learning;    logistic regression;    neural networks;    support vector machine;    510;   

Others  :  http://s-space.snu.ac.kr/bitstream/10371/131490/1/000000021891.pdf

美国|英语

来源: Seoul National University Open Repository

【 摘 要 】

In this thesis, we discuss the credit ratings of companies. Our purpose is to make a credit rating prediction rule that gives each company a credit which is as correct as possible to the actual rank. We describe three representativemachine learning algorithms, which are ordinal logistic regression, neural networks and support vector machine. In addition, we try to analyze their performance and correctness and compare them to determine which methodis the most efficient in machine learning to decide ratings. We deal with two different data sets of experiments which consist of true credit rating of companies in 2009 and 2013 and financial information in the previous year.