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naive bayesian network
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  naivebayesian网络
     An New Intrusion Detection Method Based on ICA Model and Naive Bayesian Network
     一种基于独立分量分析和Naive Bayesian网络的入侵检测方法
短句来源
     This paper applied the method of independent component analysis to intrusion detection system. An new intrusion detection method based on independent component analysis and Naive Bayesian Network is proposed.
     文章将独立分量分析穴ICA雪模型引入入侵检测系统,提出了基于独立分量分析和NaiveBayesian网络的入侵检测分类的新方法。
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  “naive bayesian network”译为未确定词的双语例句
     It proposes a hybrid approach for regression analysis—BRT(Bayesian regression tree), which builds tree model by the divide-and-conquer method and uses NBR (naive Bayesian network for regression) to replace leaf node.
     结合朴素贝叶斯和决策树提出一种用于回归分析的混合学习方法—BRT(Bayesian Regression Tree)。 该方法基于分而治之原则构造决策树,以朴素贝叶斯取代叶节点。
     It proposes a hybrid approach for regression analysis—BRT(Bayesian regression tree),which builds tree model by the divide-and-conquer method and uses NBR (naive Bayesian network for regression) to replace leaf node.
     结合朴素贝叶斯和决策树提出一种用于回归分析的混合学习方法—BRT(Bayesian Regression Tree)。 该方法基于分而治之原则构造决策树,以朴素贝叶斯取代叶节点。
短句来源
  相似匹配句对
     Boosting Naive Bayesian Learning
     增强型朴素贝叶斯学习
短句来源
     Naive Bayesian Classiflers Using Feature Weighting
     基于特征加权的朴素贝叶斯分类器
短句来源
     On the naive art
     论素朴的艺术
短句来源
     ve Bayesian.
     ve Bayesian的贝叶斯网络的模型。
短句来源
     It is mainly of two kinds, Naive Bayesian Classification and Bayesian Belief Network Classification.
     它主要有两种分类方法:一种为朴素贝叶斯分类,另一种为贝叶斯信念网络分类。
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  naive bayesian network
We chose to use naive Bayesian network to combine the multiple cues.
      
Thus a TAN imposes a tree-structured dependence graph on a naive Bayesian network; this structure is a Markov tree.
      
Thus a naive Bayesian network assumes that all the metrics are fully indepen dent given S.
      
In our experiments, we use a very simple naive Bayesian network, which can not represent complex relationships.
      
In a naive Bayesian network, for example, no arcs are allowed between the feature variables.
      
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In order to solve the uncertainty problems in engineering diagnosis, a threelayered topological model using Bayesian diagnostic network was proposed based on condition, operation, fault, and symptom. Moreover, it used the superiority of Bayesian network in dealing with uncertainty and experts synthetically experience. The model represented the complicated relationships in engineering diagnosis intuitively. A practical example shows that its evidences for diagnosis are more sufficient...

In order to solve the uncertainty problems in engineering diagnosis, a threelayered topological model using Bayesian diagnostic network was proposed based on condition, operation, fault, and symptom. Moreover, it used the superiority of Bayesian network in dealing with uncertainty and experts synthetically experience. The model represented the complicated relationships in engineering diagnosis intuitively. A practical example shows that its evidences for diagnosis are more sufficient and its result of network inference is more consistent with practice in comparison with naive Bayesian networks, because it takes account of operating actual conditions and operation records of equipment. This model has been used successfully for diagnosis of an industrial gas turbine in a refinery of a petrochemical complex.

为了解决工程诊断中的不确定性,提出了一种基于工况-操作-故障-征兆的3层拓扑结构的贝叶斯诊断网络模型.该模型发挥了贝叶斯网络解决不确定性问题的优越性,融合了专家的经验知识,用图形化方式直观地表达了诊断中的复杂关系.应用实例表明,与传统质朴型贝叶斯诊断网络相比,该模型考虑了诊断对象的实际运行工况和操作情况,用于诊断的证据信息更充分,网络的诊断推理结果更符合诊断实际,已成功地应用于某石化公司炼油厂的烟机诊断中.

This paper applied the method of independent component analysis to intrusion detection system. An new intrusion detection method based on independent component analysis and Naive Bayesian Network is proposed. It can improve the cluster capacity by projecting the sample to the character space defined by independent component analysis. The experiment shows that the classifier based on independent component analysis model has good capacity.

文章将独立分量分析穴ICA雪模型引入入侵检测系统,提出了基于独立分量分析和NaiveBayesian网络的入侵检测分类的新方法。通过把样本投影到有独立分量分析所确定的特征空间,来提高贝叶斯网络的分类性能,从而提高了入侵检测系统的性能。实验结果表明,这种基于独立分量分析模型的分类器具有良好的分类性能。

It proposes a hybrid approach for regression analysis—BRT(Bayesian regression tree),which builds tree model by the divide-and-conquer method and uses NBR (naive Bayesian network for regression) to replace leaf node.Experiment results on UCI data sets show that it is feasible and effective.

结合朴素贝叶斯和决策树提出一种用于回归分析的混合学习方法—BRT(Bayesian Regression Tree)。该方法基于分而治之原则构造决策树,以朴素贝叶斯取代叶节点。在U CI机器学习数据集上对该方法进行了验证,取得了良好的效果。

 
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