Federated learning method, system, and readable storage medium

Abstract

The invention discloses a federation learning method, a system and a readable storage medium. The federated learning method includes the following steps: the data terminal performs federation trainingon the multi-party training samples based on the gradient descent tree GBDT algorithm, to construct a gradient tree model, wherein the data terminal is a plurality of, the gradient tree model comprises a plurality of regression trees, the regression trees comprise a plurality of partition points, and the training sample comprises a plurality of features, the features correspond to the partition points one by one; the data terminal performs joint prediction on a sample to be predicted based on the gradient tree model to determine a prediction value of the sample to be predicted. The inventioncarries out federation training on multi-party training samples through GBDT algorithm, realizes the establishment of gradient tree model, and is suitable for scenes with large data volume and can well meet the needs of realistic production environment through the gradient tree model. Forecast the sample to be forecasted jointly, and realize the forecast of the sample to be forecasted.

Description

technical field [0001] The invention relates to the technical field of big data processing, in particular to a federated learning method, system and readable storage medium. Background technique [0002] Currently, the federated machine learning solutions for privacy protection are mainly in theoretical research and academic papers. According to research findings, limited by technical forms and practical applications, there are currently no relevant technical applications in the industry. [0003] Currently, existing privacy-preserving federated learning schemes often appear in academic papers, most of which focus on simple algorithm models such as logistic regression, or simple construction methods for single decision trees, such as ID3 and C4.5. Insufficient understanding of practical problems, more stay in the theoretical stage, lack of thinking about the real production environment, it is difficult to directly apply to the actual application scenarios in the industry. ...

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to provide a federated learning method, system and readable storage medium, aiming to solve the technical problem in the prior art that the training efficiency of samples corresponding to one or both parties is low

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