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BNT_SLP.tar
- 动态贝叶斯网络结构学习算法，用来检验基于BOA的DBN结构寻优体系的合理性与可行性。环境matlab 6.1以上-Dynamic Bayesian network structure learning algorithm, the DBN used to test the structure-based optimization BOA system is reasonable and feasible. Environmental matlab 6.1 or above
K2
- 贝叶斯网络学习算法——k2算法，包括对贝叶斯网络结构的学习，最后生成网络-Bayesian network learning algorithm- k2 algorithms, including Bayesian network structure learning, the last generation network
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- 一种贝叶斯网络结构学习MultiExpert方法 希望对大家有用-A MultiExpert approach for Bayesian Network Structural Learning
Bayes
- 在matlab开发环境下 对贝叶斯网络结构进行学习 推理 计算分类，并且对它进行性能分析和比较-Matlab development environment for learning Bayesian network structure inference to calculate the classification, and its performance analysis and comparison
K2
- 贝叶斯网络结构学习，及参数学习K2算法matlab代码-Bayesian network structure learning and parameter learning K2 algorithm matlab code
BayeK2
- 贝叶斯网络学习算法――k2算法，包括对贝叶斯网络结构的学习，最后生成网络-Bayesian network learning algorithms- k2 algorithm, including learning of Bayesian network structure, and finally generate network
learn_struct_K2
- 贝叶斯网络结构学习K2算法源码，可以用于因果判断等-K2 Bayesian network structure learning algorithm source codeCan be used to determine cause and effect, etc.
HCgai
- 贝叶斯网络结构学习爬山算法的改进方法，更准确-Improved Bayesian network structure learning climbing algorithm, more accurate
learn_struct_K2
- 本程序是贝叶斯网络结构学习的K2算法程序，可获取离散变量的贝叶斯网络-This procedure is K2 Bayesian network structure learning algorithm program, available discrete variables Bayesian Network
K2
- 从数据样本中随机选取一本分数据，运用K2算法进行贝叶斯网络结构学习-A sub-data randomly selected the data samples, using K2 Bayesian network structure learning algorithm
ACO-master
- 从数据学习贝叶斯网络结构的蚁群优化实现 matlab平台下(Ant Colony Optimisation implementation for learning Bayesian Network structures from data)
K2算法
- 本程序是贝叶斯网络结构学习的K2算法程序，可获取离散变量的贝叶斯网络。包含K2算法的matlab代码，和使用的例子，共学习使用
StructureLearningLibraries-master
- 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 effec