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贝叶斯网的关联规则是基于贝叶斯公式的一种概率化数据模型,它将复杂的、不确定的参数,通过贝叶斯网的关联规则成为具体、形象的数据图形,是解决不确定事件、复杂事件的重要方法。基于此,通过对贝叶斯网的关联规则的计算方法、应用等进行研究,为建立更好地数据挖掘系统奠定理论基础,并且形象地表明该关联规则对计算机科学领域、医药领域以及人工智能工业控制等领域的发展具有重大意义。
The Bayesian network association rules are a kind of probabilistic data model based on the Bayesian formula. It will be complex and uncertain parameters, through the Bayesian network association rules become specific, the image of the data graphics is to solve An important way to determine events, complex events. Based on this, through the study of Bayesian network association rules calculation methods, applications, etc., to lay a theoretical foundation for the establishment of a better data mining system, and vividly show that the association rules for computer science, medicine and artificial intelligence Industrial control and other fields of great significance.