The Application Of Bayes Discriminant Analysis In The Forecasting Financial Distress Of Listed Companies

It is a problem that many enterprises and researchers pay close attention to whether the listed companies have the risk to enter the financial distress.If we can predict financial distress in a timely manner,enterprises can take effective measures to avoid financial difficulties ahead of time.Before us,many researchers have done some research on this problem in different ways.In this paper,we use the Bayes classification method to predict the financial distress of listed companies.The classification method based on Bayes's analysis is a convenient and efficient method,which can be used in many practical applications.And the Bayes method is very effective in many applications.Although simple in theory Bayes classifier data with conditional independence requirements,in actual operation,although the condition is very difficult to set up strict,but it does not meet the conditions of many strict data still has a good classification effect.In this article,we will use Naive Bayes classification method and local linear discrim-inant analysis method in the network to find the listed company is the data,through the modeling of some of the financial variables and non-financial variables,prediction of corporate financial distress will happen in the future,and make a test.In this paper,we use some different methods to predict the data,the results show that the local linear discriminant analysis in the financial early warning of listed companies has a very high prediction accuracy.