【摘要】 提出了一种基于五层云神经网络的决策树生成方法.运用五层云神经网络学习变量间的云映射关系,从中生成云决策树.给出了神经网络的学习算法和云决策树的推理方法,这种方法不但具有神经网络的学习能力,而且结合云理论处理知识的不确定性的能力.该方法利用了五层云神经网络学习后的云映射强度,并能实现云决策树的剪枝优化,提高了算法的正确率.更多还原

【Abstract】 Cloud mapping relations among variables were learnt by a five layers cloud neural network, then cloud decision trees were extracted from that network. The learning method of neural network and the deducing method of cloud decision tree were presented, the approach combines the learning ability of neural network with the ability of cloud model which deals with the ambiguity of knowledge. The approach makes use of the weights of cloud mappings in the learnt cloud neural network, can realize the optimization of cloud decision trees by branches cutting, and improves the ratio of correctness and efficiency of induction of decision trees.更多还原