The equivalency between a decision tree for classification and a feedback neural network

In machine learning, the learning paradigms of an artificial neural network (ANN) and a decision tree (DT) are different, but they are equivalent in essence. This paper proves the approximate equivalency between feedback neural networks and decision trees. The result provides us a very useful guideline when we perform theoretical research and applications on DT and ANN.