Cross data segmentation federation learning model method, server and medium

Abstract

A cross data segmentation federation learning modeling method, a server and a readable storage medium are provided. The method comprises the following steps: the server node sends the first model parameter to each working node, so that each working node obtains the gradient and loss cost by federated model training of its own data to be trained, and feeds back the gradient and loss cost; a gradient and a cost of loss of feedback are received from each working node; the first model parameter is updated based on the gradient and the loss cost to obtain a second model parameter, and whether the second model parameter converges or not is judged. If so, the second model parameter is taken as a standard model parameter. The invention sends model parameters, collects gradient and updates model parameters through server nodes, and the working nodes carry out federated model training at the same time, so that the problem of data leakage does not exist in the model training process according todifferent types of model parameters.

Description

technical field [0001] The invention relates to the field of big data technology, in particular to a horizontal data segmentation federated learning modeling method, a server and a medium. Background technique [0002] The current machine learning solutions for privacy protection mainly remain in theoretical research and academic papers. According to research findings, existing machine learning solutions for privacy protection are limited by technical forms and practical applications, and there are currently no relevant technical applications in the industry. [0003] Moreover, the existing privacy-preserving federated learning schemes often appear in academic papers, but they have insufficient understanding of practical problems, lack of an integrated process from training to prediction, and often only stay at the theoretical research stage. Contents of the invention [0004] The main purpose of the present invention is to provide a horizontal data segmentation federated ...

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to provide a horizontal data segmentation federated learning modeling method, server and readable storage medium, aiming to solve the technical problem of lack of training process in the federated learning scheme in the prior art

Images