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The application of data mining technology based on Bayesian network structure

机译:贝叶斯网络结构在数据挖掘技术中的应用

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Data mining refers to discover unknown, effective and practical information from large database. Taking a brief introduction of data mining, and combining an explanation for data mining process and analysis of Bayesian network, it investigates the implementation of Bayesian network in this research work. Experimental results suggest that this proposed method is feasible and correct. The characteristics as its unique expression form of uncertainty knowledge, rich probabilistic expression abilities, and the incremental learning method for comprehensive priori knowledge, indicate the probability distributions and causal relations of objects, becoming one of the most striking focuses among numerous current data mining methods.
机译:数据挖掘是指从大型数据库中发现未知,有效和实用的信息。在简要介绍数据挖掘的基础上,结合对数据挖掘过程的解释和贝叶斯网络的分析,本文对贝叶斯网络的实现进行了研究。实验结果表明,该方法是可行和正确的。特征作为不确定性知识的独特表达形式,丰富的概率表达能力以及用于综合先验知识的增量学习方法,表明对象的概率分布和因果关系,成为当前众多数据挖掘方法中最引人注目的焦点之一。

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