The invention discloses a configuration method of a fault-tolerant mechanism based on a complete binary tree. The configuration method comprises the following steps of: setting a manager manger, creating n containers, deploying the n containers on different machines, marking the containers as nodes, equally dividing a data set into n parts, and setting a node control table; sorting the data sets,respectively sending the first n data set subsets into the nodes, and setting the time slice T of a period; building a neural network, obtaining parameters through forward propagation, updating the parameters through a stochastic gradient descent algorithm, building the nodes into the form of a complete binary tree, enabling each tree node to be of the same data structure; establishing communication protocols are on different hosts, enabling child nodes to carry out message transmission and model transmission in different periods respectively, and carrying out safety detection; and combining segmented models into a complete model after confirming safety, taking the complete model as a hidden layer of the current neural network to perform transfer learning training. According to the methodof the technical schemes of the invention, the error-tolerant rate of model training can be improved, and the data processing capacity of the model is improved.