Study of Inflation Risk Prediction Based On Dynamic Naive Bayesian Classifier
To keep price stability is the most important goal of monetary authority in many developed countries around the world.As a developing country,China had faced the risk of inflation frequently in recent 30 years,and for the benefit of sustained economic development,it is very necessary to find a way to predict the future changes of price and measure the risk of inflation accurately and reliably.The dynamic naive Bayesian classifier is the combination of naive Bayesian classifier and time series.It can effectively use dynamic and static information and is a powerful tool for time series prediction.In this paper,based on Gaussian kernel function to estimate the conditional density of attributes,a dynamic naive Bayesian classifier with multi smoothing parameters is presented.The inflation risk in China is predicted and analyzed by using dynamic naive Bayesian classifier.The results show that dynamic naive Bayesian classifier has very good performance.
inflation risk dynamic naive Bayesian classifier output gap money supply
Wang Shuangcheng
Shanghai Lixin University of Commerce
国内会议
上海
英文
822-837
2012-11-02（万方平台首次上网日期，不代表论文的发表时间）