The results show that the results predicted by Bayes model are both in good agreement with the practical conditions and the results obtained from the neural network model and fuzzy probability model.
研究结果表明，该模型判别预测结果与人工神经网络模型及模糊概率模型的判别结果及实际岩爆情况较吻合。
Bayes classifier model is a powerful tool for classifying attack types in intrusion detection.
贝叶斯分类模型是入侵检测中用于攻击类型分类的有力工具。
In combination with the Bayes estimator for the parameter of linear exponential model under the same loss function, the nonparametric empirical Bayes estimator of the unknown parameter was obtained.
然后结合线性指数模型未知参数在相同损失函数之下的贝叶斯估计得到了未知参数的非参数经验贝叶斯估计。
Bayes factor is the major tool for model selection in Bayesian Statistics.
在贝叶斯统计学中，贝叶斯因子是进行模型选择的主要工具。
This paper establishes dynamic forward feedback correction model with the method of combining Bayes regularization and BP neural network.
文中采用贝叶斯正则化与BP网络结合的方法，建立动态前馈校正模型。
We embed Bayes learning mechanism on the basis of the negotiation model, and elaborate process descriptions of evaluating offers, belief revision and proposing counter-offers are presented.
在该协商模型的基础上引入贝叶斯学习机制，并分别对更新信念、生成提议等协商过程作了详细阐述。
Based on nonlinear prediction ideas of reconstructing phase space, this paper presents a time delay BP neural network model, whose generalization is improved utilizing Bayes' regularization.
基于相空间重构的非线性预报思想，建立一个时滞的BP神经网络模型，采用贝叶斯正则化方法提高BP网络的泛化能力。
So a new Bayesian model mixed tree augmented Naive Bayes classifier(MTANC) based on the rough set theory is presented.
因此，提出了一种基于粗糙集理论的混合树增广朴素贝叶斯分类模型（MTANC）。
Most of the content-based filtering algorithms are based on vector space model, of which Naive Bayes algorithm and K-Nearest Neighbor (KNN) algorithm are widely used.
基于内容的过滤算法大多数是基于向量空间模型的算法，其中广泛使用的是朴素贝叶斯算法和K最近邻（KNN）算法。
Bayes statistics is different from generic statistical method, not only the model information and data information, but also transcendental information is used adequately.
贝叶斯统计不同于一般的统计方法，其不仅利用模型信息和数据信息，而且充分利用先验信息。
In the paper, the models of uncertain reasoning are focused, such as the reasoning model of Bayes probability, Reliability theory, D-S evidence theory and Neural Network.
本文主要涉及的不确定推理模型包括主观贝叶斯的概率推理模型，可信度理论推理模型，证据理论及其改进推理模型以及神经网络推理模型。
Naive Bayes classification is a kind of simple and effective classification model. However, the performance of this model may be poor due to the assumption on the condition independence.
朴素贝叶斯分类是一种简单而高效的分类模型，然而条件独立性假设在现实中很少出现，致使其性能有所下降。
This article introduced the theory of naive Bayes and discussed two popular models: multinomial model (MM) and Bernoulli model (BM) in details, implemented runnable code and performed some data tests.
本文详细介绍了朴素贝叶斯的基本原理，讨论了两种常见模型：多项式模型(MM)和伯努利模型(BM)，实现了可运行的代码，并进行了一些数据测试。
In designing web Classifier, this thesis makes use of Vector Space Model to represent the web text, which improves the performance of Bayes Classifier.
在文本分类器的设计中，用传统信息检索的空间向量模型改进了朴素贝叶斯分类器，提高了它的分类精度。
In order to implement the parameter estimate in cable fault location system, an improved Bayes algorithm used for Model parameter estimate is proposed in this paper.
为实现电缆故障定位系统的参数估计，提出了一种用于模型参数估计的改进贝叶斯算法。
In order to implement the parameter estimate in cable fault location system, an improved Bayes algorithm used for Model parameter estimate is proposed in this paper.
为实现电缆故障定位系统的参数估计，提出了一种用于模型参数估计的改进贝叶斯算法。
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