文件名称:StructureLearningLibraries-master
介绍说明--下载内容均来自于网络,请自行研究使用
贝叶斯网络又称信度网络,是Bayes方法的扩展,是目前不确定知识表达和推理领域最有效的理论模型之一。从1988年由Pearl提出后,已经成为近几年来研究的热点.。一个贝叶斯网络是一个有向无环图(Directed Acyclic Graph,DAG),由代表变量结点及连接这些结点有向边构成(Bayesian network, also known as belief network, is an extension of Bayes method and one of the most effective theoretical models in the field of uncertain knowledge expression and reasoning. Since it was proposed by pearl in 1988, it has become a research hotspot in recent years. A Bayesian network is a directed acyclic graph (DAG), which is composed of representative variable nodes and directed edges connecting these nodes)
相关搜索: 贝叶斯网络结构学习
(系统自动生成,下载前可以参看下载内容)
下载文件列表
文件名 | 大小 | 更新时间 |
---|---|---|
StructureLearningLibraries-master | 0 | 2017-05-26 |
StructureLearningLibraries-master\BayesianNetwork.py | 1254 | 2017-05-26 |
StructureLearningLibraries-master\README.md | 133 | 2017-05-26 |
StructureLearningLibraries-master\averagedBayesianNetwork.py | 3073 | 2017-05-26 |
StructureLearningLibraries-master\edge.py | 126 | 2017-05-26 |
StructureLearningLibraries-master\incrementalNetwork.py | 5588 | 2017-05-26 |
StructureLearningLibraries-master\runNetworks.py | 2090 | 2017-05-26 |
StructureLearningLibraries-master\sampledNetwork.py | 4998 | 2017-05-26 |
StructureLearningLibraries-master\testNetwork.py | 2521 | 2017-05-26 |
StructureLearningLibraries-master\vertex.py | 6730 | 2017-05-26 |