Bayesian filtering is plenty useful.
贝叶斯滤波十分的有用。
The learning of Bayesian Networks.
贝叶斯网络的学习。
We review the concepts of Bayesian tracking.
介绍了贝叶斯跟踪基本概念。
The general static Bayesian game model is established for bidding quotation.
建立了投标报价一般静态贝叶斯博弈模型。
Unlike earlier studies, Gregory used a branch of statistics called Bayesian analysis.
与较早的研究不同的是，格列格雷运用了统计学的一种方法——贝叶斯过滤分析法。
The Bayesian spam filtering technique works by comparing "spam" words with "normal" words.
Bayesian垃圾邮件过滤技术通过将“垃圾邮件”单词与“正常”单词进行比较来实现过滤任务。
Finally introduced the fundamental step of filtering spam mail with Bayesian algorithm.
最后介绍了贝叶斯过滤算法反垃圾邮件的基本步骤。
So application of Bayesian Networks for reasoning and diagnosis has a definite pertinence.
因此采用贝叶斯网络推理和诊断具有一定的针对性。
As a side benefit, a Graham-style Bayesian filter is also simpler and faster than SpamAssassin.
附带的好处是，graham样式的贝叶斯过滤器还是比SpamAssassin更快和更简单。
This paper investigates the credit scoring accuracy of three naive Bayesian classifier models.
论文研究了三种朴素贝叶斯分类器信用评估模型的精度。
Bayesian network is one of the most efficient models in the uncertain knowledge and reasoning field.
贝叶斯网络是目前不确定知识和推理领域最有效的理论模型之一。
Both likelihood ratio tests and Bayesian inference are employed to study the phylogeny of Phasianidae.
应用似然比检验和贝叶斯推论进行雉科分子系统学研究。
This approach is superior to the apparently "complex" methods such as Bayesian networks or neural networks.
这种方式倾向于 “复杂的”方法，比如Bayesian网络或神经网络。
I decided to look into how well a much more starkly limited model space would work for a Bayesian spam filter.
我决定研究一下，对于贝叶斯垃圾邮件过滤器，一个绝对有限的模型空间究竟工作得有多好。
Bayesian statistics theory: Expatiate the mathematic principle of Bayesian Networks, Bayesian statistics.
贝叶斯统计理论：阐述贝叶斯网络的数学原理——贝叶斯统计。
The research shows that the game model has a perfect Bayesian Nash equilibrium and the existing of moral haz.
研究表明，博弈模型存在某种形式的精炼贝叶斯纳什均衡，而且道德风险的存在会使保险单价格上升。
Special versions of Bayesian networks, as it turned out, can manage causal and counterfactual relationships as well.
结果，特殊的贝叶斯网络还可以处理因果关系和反事实关系。
Bayesian is one kind of method of posteriori probability obtained from priori probability according to new information.
贝叶斯方式是依据新的信息从先验概率得到后验概率的一种方式。
For example, let's say that being in the whitelist gives a score of -10, but matching the Bayesian filter gives a score of 15.
例如，假定如果电子邮件地址在白名单中则得到- 10分，但是如果它匹配Bayesian过滤器，则得到15分。
It is compared with two kinds of classifier, which is based on the principle of immunity, and traditional Bayesian classification.
与两种基于免疫原理的文本分类方法和传统的贝叶斯分类器进行了比较研究。
In "A Plan for Spam" (see Resources later in this article), Graham suggested building Bayesian probability models of spam and non-spam words.
在“APlanforSpam”（请参阅本文后面的 参考资料）中，Graham提议建立垃圾邮件和非垃圾邮件单词的贝叶斯概率模型。
It appears to be objective. But when models are built, it is almost impossible to avoid including Bayesian-style prior assumptions in them.
但是模型建立起来后，几乎不可避免地把贝叶斯的预先假定理论也纳入了模型中。
For example, NLTK has a whole framework for text classification using statistical techniques like "naive Bayesian" and "maximum entropy" models.
例如，NLTK有一个完整的框架，用于通过类似于“naiveBayesian”和“maximumentropy”等模型的统计技术进行文本分类。
The learning of Bayesian Networks is studied, including structure learning of Bayesian Networks and parameter learning of Bayesian Networks.
研究了贝叶斯网络的学习问题，包括贝叶斯网络结构学习和贝叶斯网络参数学习。
On the customer support side, a Bayesian Filtering algorithm zaps spam and turns email into trackable cases routed to the correct department.
在客户支持方面，贝叶斯过滤（Bayesian Filtering）算法会阻击所有spam，让email能够准确投递到相应的部门。
The most common statistical approach is called bayesian inference and is explained in detail in another IBM developerWorks article (see Resources).
最常见的统计方式称为贝叶斯推理，更详细的内容，可以参阅IBMdeveloperWorks 的另一篇文章（参见参考资料）。
This paper recommended the E-mail filtering module which adopts the heuristic filtering technique based on the Bayesian Statistic method detailedly.
重点介绍了采用基于贝叶斯方法的智能启发式过滤技术的邮件过滤模块设计。
Variable correlation is expressed with consequence graph in Bayesian Networks (BN), analysis of failure mode and effect of complex system is realized.
贝叶斯网络用因果关系图的形式表达变量间相互关系，实现复杂系统的故障模式和效应分析。
Bayesian Networks is a model that efficiently represents knowledge and probabilistic inference and is a popular graphics decision-making analysis tool.
贝叶斯网络是在不确定性环境下有效的知识表示方式和概率推理模型，是一种流行的图形决策化分析工具。
Bayesian Networks is a model that efficiently represents knowledge and probabilistic inference and is a popular graphics decision-making analysis tool.
贝叶斯网络是在不确定性环境下有效的知识表示方式和概率推理模型，是一种流行的图形决策化分析工具。
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