System for realizing data set construction processing based on federated learning and construction generation method thereof

Abstract

The invention relates to a system for realizing data set construction processing based on federated learning, and the system comprises: a data set management module which is connected with a historical data set and is used for exporting and managing the data set; and a data set generation module which is connected with the data set management module and is used for participating in generation of data sets of the nodes by the nodes according to data generation rules and feeding back states to the central node. The invention also relates to a generation method for realizing data set constructionbased on federated learning. The system for realizing data set construction processing based on federated learning and the construction generation method thereof are adopted, different from the priorart that federated learning needs to be trained and used by depending on a self-owned sample set, the federated learning data set construction system provides a multi-rule and multi-mode simulation data generation mode, provides a required data set for learning and training of each federated learning node, can effectively expand a data use link, and covers various use scenes.

Description

technical field [0001] The present invention relates to the field of data processing, in particular to the field of artificial intelligence, and specifically refers to a system for realizing data set construction and processing based on federated learning and a construction and generation method thereof. Background technique [0002] Federated Learning (Federated Learning) is an emerging artificial intelligence basic technology, which was first proposed by Google in 2016. Under the premise of regularization, efficient machine learning can be carried out among multi-participants or multi-computing nodes. Federated learning requires a large amount of data sets in the training and model evaluation stages, but in actual use, data sets are often scarce resources, especially in the system acceptance stage, the existing data sets often cannot cover various training and use of algorithms Scenes. To this end, a federated learning dataset construction scheme is proposed to facilitat...

AI Technical Summary

Problems solved by technology

Federated learning requires a large amount of data sets in the training and model evaluation stages, but in actual use, data sets are often scarce resources, especially in the system acceptance stage, the existing data sets often cannot cover various training and use of algorithms Scenes

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