贝叶斯动态模型及其预测算法在数据挖掘中的应用研究

Research on Bayesian Dynamic Model and Forecasting Algorithm in Data Mining Application

通过对贝叶斯预测过程的研究,提出了应用于数据挖掘的10类贝叶斯动态模型及其预测算法、并解决了非线性动态模型的线性化问题。以该模型及算法建立的数据挖掘系统经过实例测试其效果很好,有较高的理论和实用价值,可以在政府、企业等领域内推广应用。

Based on the analysis of Bayesian forecasting procedures,this paper suggests ten different kinds of Bayesian dynamic models and forecasting algorithms which may be used in data mining applications,and gives out the answer to the linearization problems in non-linear dynamic model.Data Mining Systems building on these models and algorithms have been tested and proved to be very useful in practice and in theory.And they can be applied to the fields of gov-ernment and enterprises.