Data screening method, device and equipment and readable storage medium

Abstract

The invention discloses a data screening method. The method comprises the following steps: a first participant receives a data detection model sent by a coordinator, and detects a data set owned by the first participant based on the data detection model to obtain a reconstruction error set corresponding to the data set, and then obtaining a data screening result corresponding to the first participant based on the reconstruction error set and an error range configured by the coordinator. The invention further discloses a device, equipment and a readable storage medium. A data set owned by the participant is detected through the data detection model; therefore, the participants and the training data which have the same statistical distribution as the training set of the data detection modelare screened out for federation training, the training data of the participants are similar and different, the diversity of the training data owned by the participants can be fully utilized, the advantages of federation learning are utilized to the maximum extent, and a better model is trained.

Description

technical field [0001] The present invention relates to the technical field of machine learning, in particular to a data screening method, device, equipment and readable storage medium. Background technique [0002] In horizontal federated learning, if the training data owned by other participants cannot help themselves, then the participant will not gain anything from participating in horizontal federated learning. Therefore, before training the horizontal federated learning model, you need to choose Participants in horizontal federated learning. [0003] In the prior art, there is a common scheme: the coordinator randomly selects the participants of the horizontal federated learning from the candidate participants (or potential participants), expecting to select training data with relatively balanced statistical distribution. This scheme is very simple, but there is no guarantee that training data with a relatively balanced statistical distribution can be selected. Becau...

AI Technical Summary

Problems solved by technology

[0005] The main purpose of the present invention is to provide a data screening method, device, equipment and readable storage medium, aiming at solving the problem that in the existing horizontal federated learning, the coordinator cannot select good training data or participants' technology for horizontal federated learning question

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