First , according to the definition of n - dimensional density function , this thesis decomposes it into the conditional probability about variable alone , which can be expressed by conditional failure rate function about variable alone 本文首先根据多维密度函数的定义把它分解成关于各个变量的条件概率，而这些条件概率可以由各变量的条件失效率来表达。
Though studying some formulas in theory of probability , we give the formula conditional probability in complete event set and a simplified formula for density ' s function in two random variables , they offer new methods in calculation 摘要通过对概率论中有关公式的研究，给出了全条件概率公式和二维随机变量函数的密度函数的简化计算公式，为其计算提供了新的方法。
Furthermore , we have listed the calculating software program in algebra . the great effect can be seen in this article caused by the combination of the conditional probability generating function method and the relevant calculation software in algebra 另外，我们也给出了有关的利用代数计算软件的程序，从本文可体会到将条件概率母函数法与目前的代数计算软件相结合所产生的巨大威力。
To improve the representation capability for index relationships in enterprise performance modeling , the performance modeling method based on casual relationship was improved and an index improvement method based on conditioned probability was proposed 摘要为增强企业性能建模中性能指标之间关系的表达能力，改进了基于因果关系的性能建模方法，提出了一种基于条件概率的指标关系改进方法。
The research methods are : using the conditional probability theory to work out the moment generating function of process s ( t ) and its distribution function ; using the increasing and declining character and the convexity to compare the lundberg exponent and the ruin probability of different processes 研究方法为:利用条件概率证明过程s ( t )的矩母函数以及其分布函数;利用增减性以及凹凸性比较lundberg指数,从而比较其相关性对破产概率的影响。
By redefining the cardinality of set , we establish the relationship between the domain / range ratio and the testability metric . pie model can help us doing white box test in unit test phase . based on the fault / failure model and conditional probability , a formula is found to get testability metric , with which we prove there is a max value in software testability metric 在单元测试阶段可以运用pie模型帮助进行白盒测试,本文在软件的错误/故障模型的基础上,运用概率论中条件概率的相关知识,建立了可测试性的一个计算公式,并使用该公式证明了软件的可测试度存在一个最大值。
* the inference and learning algorithms the inference algorithm for polytree bn and its application in the model are firstly introduced . secondly , after studying the famous k2 learning algorithm the improved algorithm ( mk2 ) and its parallel implementing method have been present . what is more , the modified mdl algorithm is given *推理及学习算法详细介绍了polytree信度网的推理算法及在阻塞模型中的应用；在研究cooper后验概率学习方法（ k2学习算法）基础上，提出了改进算法（ mk2算法）及并行实现方法；研究了另一种信度网结构学习算法（ mdl学习算法）并提出了其改进算法；最后还提出了条件概率学习方法。
Monte carlo is a method that approximately solves mathematic or physical problems by statistical sampling theory . when comes to bayesian classification , it firstly gets the conditional probability distribution of the unlabelled classes based on the known prior probability . then , it uses some kind of sampler to get the stochastic data that satisfy the distribution as noted just before one by one 蒙特卡罗是一种采用统计抽样理论近似求解数学或物理问题的方法，它在用于解决贝叶斯分类时，首先根据已知的先验概率获得各个类标号未知类的条件概率分布，然后利用某种抽样器，分别得到满足这些条件分布的随机数据，最后统计这些随机数据，就可以得到各个类标号未知类的后验概率分布。
For the extend model of cognitive map , conditional probability , theory of uncertainty and knowledge database are introduced to cognitive map , and fuzzy cognitive map ( fcm ) , probabilistic fuzzy cognitive map ( pfcm ) , belief knowledge database based probabilistic fuzzy cognitive map ( bkpfcm ) , " extended dynamic cognitive network " are presented . therefore , those extended models can express the fuzzy and belief measure of uncertainty causal relationships and expert knowledge with uncertainty 本文把条件概率、不确定性理论及知识库引入认知图中，提出“概率模糊认知图” 、 “基于信任知识库的概率模糊认知图”及“扩展动态认知网络”来表示事物间因果关系测度的不确定性、因果联系的时空特性及专家对知识的不确定性，从而扩展了认知图模拟现实世界的能力。
It ' s a pity that although there are many papers and articles focused on data mining published every year , most of them deal with data mining concept and abstract algorithm theory , it is hardly to see their real implementation and application , in this context , when i was in my graduate exercitation in a company in beijing , which focus on developing supermarket software , i joined and completed an olap ( online analytical processing ) project , merchandise analysis and sale report system , which based on microsoft analysis service and microsoft sql server . i also design and implement three important algorithms : merchandise association rule algorithm based on multi - level merchandise category , supermarket member customer shopping frequent sequence generating algorithm , customer classification ( decision tree ) algorithm which based on information entropy and conditional probability tree , and they all achieve expected result 本文作者在实习期间，参与并完成了基于微软分析服务器的销售分析与报表系统；并在公司即将开始的数据挖掘项目中，完成了多个重要算法的设计和c + +程序实现：基于多层分类商品树的商品关联规则算法，会员顾客的购物频繁序列模式产生算法；基于信息熵理论和条件概率树的会员顾客分类(决策树)算法，并分别使用数据进行了测试，取得了较好的结果。
