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刘遵雄,郑淑娟,秦宾,张恒 (1.华东交通大学 信息工程学院江西 南昌3300132.江西财经大学科研处江西南昌330013) 
中文关键词:财务预警  L1范数惩罚  正则化技术  逻辑回归
L1-regularized Logistic Regression Modeling for Financial Distress Prediction
Abstract:The linear model and the generalized linear model are widely employed in data analysis and data mining in social economic and scientific research,such as Financial Distress Prediction.If L1 norm penalty is added with model parameters, It can achieve feature selection at the same time when the model coefficients are estimated. L1 norm penalized logistic regression model is proposed for financial distress prediction with listed companies in this paper. Together with normal logistic regression and L2 norm penalized logistic regression model, three logistic regression models are built and tested on the two-years-before data from ST companies and normal counterparts in China security market .The results demonstrate the performance of L1 norm penalized logistic regression model. The model can achieve better prediction accuracy and explanation ability.
keywords:financial distress prediction  L1-norm penalty  regularization technology  logistic regression
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