贝叶斯

K2 algorithm using Bayesian network built from the a priori probability to achieve reasoning, structure learning, parameter learning.

详细说明：用k2算法从先验概率构建贝叶斯网络，实现推理，结构学习，参数学习用贝叶斯方法。

The application of total probability formula and Bayes formula for sample space on which two disservements and these formulas of the sample space have proved.

讨论了样本空间有不同划分时全概公式和贝叶斯公式的应用方法，给出了样本空间有两种划分时全概公式和贝叶斯公式的证明。

Uses of Bayes formula in statistical Decisions;2. Considering the influence of the distorted information on fault location,a method for fault location in distribution network is presented based on Bayes formula .

从解决配电网故障信息发生畸变影响故障定位入手，提出了一种运用贝叶斯公式的配电网故障定位方法，并建立了利用贝叶斯公式最大显著度条件的故障定位模型。

Finishing calculation of mean value, standard deviation, skewness, kurtosis of Beta distribution.(2) Fitting parameters of many kinds of typical distribution and using residual deviation to evaluate fitting precision.(3) Using Beta distribution as an agreed indication distribution applied to many kinds of practical photoelectric measurement distributions.(4) Deriving theory formula of Bayes point estimation about Beta distribution parameters and mean value and standard deviation on the condition of mean square error loss function and supposed the prior distribution is uniform distribution.(5) Generating MCMC sample from post distribution by the method of Gibbs sample algorithm. Calculating bayes point estimation from sample on the condition of mean square error loss function. Calculating confidence interval by an approximate method to complete interval estimation.

本文的主要工作有：(1)解决了Beta分布参数a和b的精确计算以及均值、标准差、偏度、峰度的计算问题；(2)拟合出10余种典型分布的Beta分布的两个参数，并且采用剩余标准差评价该Beta分布的拟合精度；(3)对多种典型的光学与光电测量系统的测量分布进行了Beta分布统示表示；(4)在假设先验分布为均匀分布前提下，得到参数a和b以及均值μ和标准差σ在均方误差损失函数下的贝叶斯点估计理论计算公式；(5)利用直接抽样的Gibbs抽样算法，从后验分布中产生MCMC样本，从样本直接计算均方误差损失函数下的贝叶斯点估计，并使用一种近似方法计算其置信区间，完成区间估计。

Spam ; Bayesian Classifying Method ; Vector Space Model ; Naive Bayesian Method

垃圾邮件；贝叶斯分类；向量空间模型；朴素贝叶斯分类

Pixel values in an image window are taken as a realization of a BN, and the structure and parameters of BN for each texture class are then studied. The conditional distribution probability of the pixels is used as the feature for texture classification.

把纹理图像在一个窗口内各个像素的灰度值看作贝叶斯网络的一次实现，通过训练得到各类纹理所对应贝叶斯网络的结构和参数，用纹理图像像素点在网络中的条件概率分布作为特征进行纹理分类。

Every research result shows that Bayesian Classifier acts as one important class technology, Compared with Decision Tree Construction and Neural Network Classifier, Bayesian Classifier can adequately bring into play its incertitude discursion ability, so it can ameliorate learning ability and increase accuracy of forecast, it have better class effect in some conditions.

各种研究结果表明：贝叶斯分类作为数据挖掘中一项重要的分类技术，与决策树和神经网络分类器相比，贝叶斯网络分类器可以充分发挥它的不确定性推理能力，从而改善学习效果，提高预测准确率，在某些情况下具有更好的分类效果。

Bayesian and empirical Bayesian theory are used to estimate the scale parameter of the double exponential distribution and the loss function and risk function of the Weibull distribution.

中文摘要：本文将贝叶斯，经验贝叶斯理论应用于双指数分布族的刻度参数估计和Weibull分布的损失函数和风险函数的估计。

In this paper I introduce basic theory of Bayes' method and business risk. I give out the thought of essential solving steps, then combine with an instance, as a spinning mill which would produce two different manufactures, flower woolen cloth and gabardine. I adopt Bayes' expectation of loss method to analysis the two manufactures producing, then made a decision, figure out expectation value of the two schemes. Then select a plan which get best profit or least loss. I compute other indexes, for example, probabilities under different stations, tenderness analysis, risk degree of different plans, then compare those indexes, we make a decision.

在文中详细的介绍了贝叶斯方法的基础理论和企业风险的有关理论，给出了贝叶斯估计方法的基本解题思路和步骤，再结合具体实例，对某纺织厂公司生产两种产品，花呢和华达呢具体生产的决策问题采用贝叶斯期望损益分析法，计算出两种方案的期望值，选取收益最大或损失最小的决策方案为最优决策方案，在不同的自然状态下，再计算其他的指标，例如敏感度分析，风险度。

In chapterⅡ, considering GLMMs data which the number of high units is different and the number of low units is small and unbalanced, we Conduct a series of simulations, the simulations show that regardless of the number of the level 2 units,the Bayesian estimate of random effects residual variance is more precise than PQL and the PQL estimation deviates from the true value seriously; In terms of the fixed effects estimates, When the number of level 2 units is 20, The mean and median of the Bayesian estimate is more precise than PQL,But With the number of level 2 units increase,the estimate of two methods is similar. Thus, in practical applications, we recommend the use of Bayesian method.

第二章针对不同高水平单位数，低水平数较小且不平衡的GLMMs数据，进行模拟研究，研究表明：无论水平2单位数的大小，贝叶斯方法随机效应残差方差估计值远比PQL法更接近真实值，PQL法严重偏离了真实值；而对固定效应参数估计值，当水平2单位数为20时，贝叶斯法各参数的均数和中位数均要较PQL法更接近真实值，而随着水平2单位数的增加，两种方法在估计固定效应参数时相差并不大，因而，在实际应用中，推荐采用贝叶斯法。

On the other hand, the more important thing is because the urban housing is a kind of heterogeneity products.

另一方面，更重要的是由于城市住房是一种异质性产品。

Climate histogram is the fall that collects place measure calm value, cent serves as cross axle for a few equal interval, the area that the frequency that the value appears according to place is accumulated and becomes will be determined inside each interval, discharge the graph that rise with post, also be called histogram.

气候直方图是将所收集的降水量测定值，分为几个相等的区间作为横轴，并将各区间内所测定值依所出现的次数累积而成的面积，用柱子排起来的图形，也叫做柱状图。