Enterprise Financial Early Warning Based on Lasso Regression Screening Variables

Abstract

The construction of an enterprise financial warning model is very important for a listed company, and this paper uses the financial data of 2819 listed enterprises as a sample, uses the lasso method for model index screening and uses a variety of classical classification methods and machine learning methods to build the model and analyze its discriminating effect. The results show that the lasso method can effectively reduce the multicollinearity between variables while reducing dimensionality and the classification effect of machine learning method is better than the classical classification method.