CPD:条件概率分布

条件概率分布(Conditional Probability Distribution,常缩写为CPD)是指某一随机变量在给定其他变量取值情况下的概率分布。为便于书写与使用,该术语在跨学科领域(如统计学、机器学习和人工智能)中广泛采用其英文缩写CPD。其核心思想在于描述变量间的条件依赖关系,是概率图模型和贝叶斯推断中的基础概念,对于建模复杂系统中的不确定性具有重要作用。

Conditional Probability Distribution具体释义

  • 英文缩写:CPD
  • 英语全称:Conditional Probability Distribution
  • 中文意思:条件概率分布
  • 中文拼音:tiáo jiàn gài lǜ fēn bù
  • 相关领域cpd 未分类的

Conditional Probability Distribution的英文发音

例句

  1. At last the learning method for conditional probability distribution is investigated.
  2. 最后还提出了条件概率学习方法。
  3. The missing measurements are described by a binary switching sequence satisfying a conditional probability distribution.
  4. 系统的不完全量测用满足特定条件概率分布(CPD)的二值切换的随机序列来描述。
  5. This paper deals with the calculating method of the Pearson type ⅲ conditional probability distribution curve of streamflow.
  6. 本文讨论径流皮尔逊Ⅲ型条件概率分布(CPD)曲线的计算方法。
  7. Existence of B-valued random variable with regular conditional probability distribution
  8. B值随机变量正则条件概率分布(CPD)的存在性
  9. Bayesian network is a directed acyclic graph, it can use a conditional probability distribution directly express the dependencies between variables.
  10. 贝叶斯网络是一个有向无环图,能够通过一个条件概率分布(CPD)直观地表达各个变量之间的依赖关系。