The learning of Bayesian Networks is an important tache, which combines training data with prior knowledge and model evaluation to acquire the structure hidden in data and parameters.
贝叶斯网络的学习是数据挖掘中非常重要的一个环节，是将先验知识和模型评价融入训练数据，获得数据中隐藏的拓扑结构和参数的过程。
A novel three-layer neural network with knowledge-based neurons (NNKBN) in hidden layer has been applied to model the crossover discontinuities in stripline circuits.
本文采用一种新型的三层神经网络，即隐蔽层具有知识神经元的神经网络(NNKBN)模拟带状线电路中的十字交越不连续性。
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