后验概率

So, if know semiotic condition of the patient, what can be based on card of M* plan cipher out to await concealed variable is posterior probability distribution, reach thereby differentiate card result.

所以，假如知道病人的症状情况，就可以基于M*计算出证候隐变量的后验概率分布，从而得出辨证结果。

In the process, we calculate the posterior probability of semantics by unlabeled samples information.

在计算的过程中，使用了未标记样本的信息计算语义出现的后验概率。

Based on the data of posterior probability, we use the finite mixture modes to model the data.

2根据利用高斯混合判别分析得到的影像的后验概率，利用有限混合模型对数据进行建模。

Then, the optimized weights are determined by the posterior probability of these samples.

最后，波束成形器的最优权值由这些样点的后验概率加权获取。

The diagnosis modeling procedure, modeling method for HMT and computational methods for Bayesian posterior probability are also given.

给出了诊断模型的建模步骤、HMT模型的建立方法和Bayes后验概率的计算方法。

In this paper we specify the posterior probability to be Gaussian mixtures and using a standard EM algorithm to fit the corresponding parameters of the mode.

在试验中假设影像的后验概率符合混合高斯分布，并利用EM算法化解模型中的参数。

Thefirst algorithm considers that the process of synthesizing novel views can be regularized toa maximum posterior probability problem.

基于图像学习的方法将生成中间视图表达为一个最大后验概率的问题。

The emphasis of this paper is as follows: Firstly, an improved AR model and Bayesian posterior probability based clustering method is proposed and the principle and way of how to use this method for clustering time course gene expression data are elaborated.

本论文重点是：建立了一种改进的基于自回归模型和贝叶斯后验概率的动态聚类分析算法，阐述了应用该算法进行时序基因表达数据聚类分析的原理和方法；建立了一种基于自回归模型的模糊动态聚类分析算法，阐述了应用该算法进行时序基因表达数据聚类分析的原理和方法。

In chapter three, because of need data packet in the process of parameter estimation, but M-step involved the posterior probability calculate, it increases the computing complexity and affects the efficiency of the algorithm.

在第三章中，由于用EM算法在混合模型参数估计中涉及到运用后验概率密度实现数据分组，加大了计算的复杂度，影响了算法的效率。

We can identify the cointegration rank of a model by posterior probability of cointegration rank; Thus Cointegration relation can be identified.

通过协整秩的后验概率识别模型的协整秩，从而对协整关系加以识别，实证表明这种方法的模型识别率还是相当高。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。