贝叶斯推断 Bayesian inference
贝叶斯推断(英语:Bayesian inference)是统计推断的一种,其通过某些观察的值来确定某些假设的概率,或者使这些概率更接近真实值。在计算概率的过程中会使用贝叶斯定理,贝叶斯定理是由统计学家托马斯·贝叶斯(Thomas Bayes)根据许多特例推导而成,后来被许多研究者推广为一普遍的定理
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词汇 | Bayesian learning |
分类 | 英语词汇 英语翻译词典 |
释义 |
Bayesian learning
中文百科
贝叶斯推断 Bayesian inference(重定向自Bayesian learning)
贝叶斯推断(英语:Bayesian inference)是统计推断的一种,其通过某些观察的值来确定某些假设的概率,或者使这些概率更接近真实值。在计算概率的过程中会使用贝叶斯定理,贝叶斯定理是由统计学家托马斯·贝叶斯(Thomas Bayes)根据许多特例推导而成,后来被许多研究者推广为一普遍的定理
英语百科
Bayesian inference 贝叶斯推断(重定向自Bayesian learning)
![]() ![]() ![]() ![]() Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. Bayesian inference is an important technique in statistics, and especially in mathematical statistics. Bayesian updating is particularly important in the dynamic analysis of a sequence of data. Bayesian inference has found application in a wide range of activities, including science, engineering, philosophy, medicine, sport, and law. In the philosophy of decision theory, Bayesian inference is closely related to subjective probability, often called "Bayesian probability". |
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