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学习贝叶斯网络

Learning Bayesian Networks
课程网址: http://videolectures.net/kdd07_neapolitan_lbn/  
主讲教师: Neapolitan Richard E
开课单位: 东北伊利诺伊大学
开课时间: 2007-08-12
课程语种: 英语
中文简介:
贝叶斯网络是用来表示大量变量之间的概率关系并用这些变量进行概率推理的图形结构。1990年代出现了从被动数据中学习贝叶斯网络的优秀算法。我将使用一种直观的方法来讨论基于约束的学习方法,该方法专注于因果学习。然后我将用一些简单的例子讨论贝叶斯方法。我将展示如何使用贝叶斯方法,我们甚至可以从两个变量的被动数据中学习一些因果影响。最后,我将展示一些财务和营销应用程序。
课程简介: Bayesian networks are graphical structures for representing the probabilistic relationships among a large number of variables and doing probabilistic inference with those variables. The 1990's saw the emergence of excellent algorithms for learning Bayesian networks from passive data. I will discuss the constraint-based learning method using an intuitive approach that concentrates on causal learning. Then I will discuss the Bayesian approach with some simple examples. I will show how, using the Bayesian approach, we can even learning something about causal influences from passive data on two variables. Finally, I will show some applications to finance and marketing.
关 键 词: 贝叶斯网络; 概率关系; 因果学习; 金融和营销
课程来源: 视频讲座网
最后编审: 2019-12-19:lxf
阅读次数: 74