A Machine Learning Based Enterprise Bond Default Warning Model
This study aims to construct a corporate bond default warning model using big data methods,utilizing machine learning algorithms such as logistic regression,XGboost,and support vector machines,combined with multidimensional data such as enterprise electricity and finance,to establish a corporate default warning indicator system,train and predict the default probability of current corporate bonds,classify enterprise risk levels,and reduce investment risks.
bond defaultinvestment risklogistic regressionXGBoost algorithmSupport vec-tor machine
NETL
NSTL
万方数据
