On the solution of the XOR problem using the decision tree-based neural network

The decision tree-based neural network is introduced to combine neural networks with decision trees. Its key idea is using decision trees to form the structure of the neural network: to construct a decision tree and then convert the tree into a neural network. The decision tree and neural network for classification are similar and have equivalent property. Thereby a decision tree can be used to provide a systematic design method of neural network. We propose a new mapping between decision tree and neural network that can accurately specify the number of units, layers, connection and initial setting of parameters of neural network. Furthermore, we quote two theorems to show that the mapping is reasonable. In this paper, we use the decision tree-based neural network to solve the XOR problem.