Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Multi-party joint modeling method and device based on federated learning and medium

A modeling method and federated technology, applied in the field of machine learning of financial technology, can solve problems such as low computational efficiency

Pending Publication Date: 2020-07-03
WEBANK (CHINA)
View PDF0 Cites 28 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The main purpose of this application is to provide a multi-party joint modeling method, device and medium based on federated learning, aiming to solve the technical problem of low computational efficiency in the construction of vertical federated modeling algorithm models in the prior art

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Multi-party joint modeling method and device based on federated learning and medium
  • Multi-party joint modeling method and device based on federated learning and medium
  • Multi-party joint modeling method and device based on federated learning and medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0080] 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.

[0081] The embodiment of the present application provides a multi-party joint modeling method based on federated learning. The multi-party joint modeling method based on federated learning is applied to the first device for vertical federation. In this application, the multi-party joint modeling method based on federated learning For the first example, refer to figure 1 , the multi-party joint modeling method based on federated learning includes:

[0082] Step S10, performing sample alignment on each second device associated with the first device to obtain first sample data;

[0083] In this embodiment, it should be noted that the second device can communicate with the first device, and the first device and each of the second devices can perform longitudinal federated learning, and in this embodi...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a multi-party joint modeling method and device based on federated learning and a medium. The multi-party joint modeling method based on federated learning comprises the steps that multi-party joint modeling is carried out, and performing sample alignment with each second device associated with the first device to obtain first sample data, interacting with each second devicebased on the first sample data to perform longitudinal federation, and calculating a feature splitting gain histogram to construct a joint modeling decision tree. The technical problem that the calculation efficiency is low when a longitudinal federation modeling algorithm model is constructed is 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 multi-party joint modeling method, device and medium based on federated learning. Background technique [0002] With the continuous development of financial technology, especially Internet technology finance, more and more technology [0003] (such as distributed, blockchain, artificial intelligence, etc.) are applied in the financial field, but the financial industry also puts forward higher requirements for technology, such as the distribution of corresponding to-do items in the financial industry. [0004] With the continuous development of computer software and artificial intelligence, the application of machine learning modeling is becoming more and more extensive. Among them, the GBDT (Gradient Boosting Decision Tree, gradient boosting iterative decision tree) algorithm is often used in application scenarios such a...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N20/00
CPCG06N20/00G06F18/24323G06F18/214
Inventor 马国强范涛魏文斌谭明超郑会钿陈天健杨强
Owner WEBANK (CHINA)
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com