Bayesian Network learning mainly includes structure learning and parameter learning.
贝叶斯网络学习包括网络的结构学习和参数学习。
参考来源 - 基于量子遗传算法的贝叶斯网络结构学习In the process of modeling BNs, the structure learning and parameter learning of BNs are analyzed detailedly.
详细分析了贝叶斯网络的建模过程,即贝叶斯网络的结构学习过程和贝叶斯网络的参数学习过程。
参考来源 - 软件项目风险管理理论与模型研究·2,447,543篇论文数据，部分数据来源于NoteExpress
The learning of Bayesian Networks is studied, including structure learning of Bayesian Networks and parameter learning of Bayesian Networks.
研究了贝叶斯网络的学习问题，包括贝叶斯网络结构学习和贝叶斯网络参数学习。
In essence, the model is to blend self-access and collaborative leaning, structure and non-structure learning, learning source and learning environment.
其实质就是混合自主学习和课堂合作学习、混合结构化学习内容与非结构化学习内容、混合多种摄影教学资源和学习环境。
The structure learning decides the proper connection types and the number of hidden units which represent fuzzy logic rules and the number of fuzzy partitions.
结构学习确定了表示了模糊规则和模糊分段数的连接类型以及隐节点数目。
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