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Federal modeling method and device based on stepwise regression method and readable storage medium

A technology of step-by-step regression and modeling method, applied in the field of machine learning of financial technology, which can solve the problems of poor effect and low efficiency of vertical federation modeling.

Pending Publication Date: 2020-07-24
WEBANK (CHINA)
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  • Claims
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AI Technical Summary

Problems solved by technology

[0004] The main purpose of this application is to provide a federated modeling method, device and readable storage medium based on the stepwise regression method, aiming to solve the technical problems of low efficiency and poor effect of longitudinal federated modeling in the prior art

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  • Federal modeling method and device based on stepwise regression method and readable storage medium
  • Federal modeling method and device based on stepwise regression method and readable storage medium
  • Federal modeling method and device based on stepwise regression method and readable storage medium

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Embodiment Construction

[0091] It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

[0092] The embodiment of this application provides a federated modeling method based on stepwise regression method, refer to figure 1 , in the first embodiment of the federated modeling method based on the stepwise regression method of the present application, the federated modeling method based on the stepwise regression method is applied to the first device, and the federated modeling method based on the stepwise regression method includes:

[0093] Step S10, acquiring the model to be trained, and receiving the feature data set of the label to be removed and the feature data set of the label to be added sent by the third device coordinated and associated with the first device;

[0094] In this embodiment, it should be noted that before performing the step of receiving the set of tag feature data...

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Abstract

The invention discloses a federated modeling method and device based on a stepwise regression method and a readable storage medium. The federated modeling method based on the stepwise regression method comprises the steps that federated modeling is carried out, obtaining model to be trained, receiving a to-be-rejected label feature data set and a to-be-added label feature data set sent by a thirddevice; the method is based on a to-be-rejected label feature data set and a to-be-added label feature data set. Longitudinal federation modeling is carried out through second equipment; executing a preset cyclic training process on the to-be-trained model, eliminating each target elimination feature meeting a preset elimination contribution degree standard in the to-be-trained model; or adding each target adding feature meeting a preset adding contribution degree standard into the to-be-trained model to circularly update the to-be-trained model until the circularly updated to-be-trained modelmeets a preset circular ending condition, and obtaining a target modeling model. The technical problems that longitudinal federation modeling is low in efficiency and poor in effect are solved.

Description

technical field [0001] The present application relates to the field of machine learning technology of financial technology (Fintech), and in particular to a federated modeling method, device and readable storage medium based on stepwise regression method. Background technique [0002] With the continuous development of financial technology, especially Internet technology and finance, more and more technologies (such as distributed, blockchain, artificial intelligence, etc.) Requirements, such as the distribution of corresponding to-do items in the financial industry also have higher requirements. [0003] With the continuous development of Internet technology and finance, the application of federated learning is becoming more and more extensive. In the vertical federated learning scenario, both the label provider and the feature provider participating in the federated learning will provide training features, and based on these training features through the Federated learnin...

Claims

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Application Information

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IPC IPC(8): G06N20/00
CPCG06N20/00
Inventor 吴玙范涛马国强魏文斌谭明超郑会钿陈天健杨强
Owner WEBANK (CHINA)
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