Federal learning feature selection method, device and system and electronic equipment
A feature selection method and learning system technology, applied in machine learning, instrumentation, computing, etc., can solve problems such as low rationality and achieve the effect of improving rationality
Pending Publication Date: 2022-05-13
杭州博盾习言科技有限公司
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Problems solved by technology
[0004] Embodiments of the present invention provide a federated learning feature selection method, device, system and electronic equipment to solve the problem of low rationality of feature selection in the federated learning process in the prior art
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[0072] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention. It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and related data involved in the embodiments of the present invention are all information authorized by the user or authorized by all parties.
[0073] refer to figure 1 , shows a flowchart of steps of a federated learning feature selection method of the present invention. The federated learning feature selection method...
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The embodiment of the invention provides a federal learning feature selection method, device and system and electronic equipment. The method comprises the following steps: respectively acquiring local preset user features through a participant and an initiator; according to preset user features, presetting target evaluation parameter values corresponding to the user features; based on the target evaluation parameter value, determining a target evaluation score corresponding to each preset user feature; and according to the target evaluation score, selecting a feature of which the target evaluation score meets a preset condition as a target user feature. According to the embodiment of the invention, the target evaluation score corresponding to each preset user feature is calculated based on the target evaluation parameter value, and then the target user feature is selected according to the target evaluation score for model training. Therefore, the reasonability of feature selection during federal learning modeling is improved, and the situation of unreasonable feature selection caused by offline communication and random user feature selection in the prior art is avoided.
Description
technical field [0001] The present invention relates to the technical field of machine learning, in particular to a federated learning feature selection method, device, system and electronic equipment. Background technique [0002] With the continuous development of artificial intelligence technology, more and more fields have begun to carry out various businesses based on related models of artificial intelligence. For example, due to the simplicity of its model and the interpretability of variables, the scorecard has become a common method for identifying user qualifications in the financial world, and it can be used both before and after a loan. [0003] At the same time, in today's data silo scenario, the need to model federated scorecards is growing rapidly based on customers' growing need for federated modeling. The federated learning method in the existing technology is only that each participant selects user characteristics based on offline communication, etc. This s...
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Login to View More IPC IPC(8): G06K9/62G06N20/00
CPCG06N20/00G06F18/211G06F18/24323G06F18/214
Inventor 周一竞张宇孟丹李宏宇李晓林
Owner 杭州博盾习言科技有限公司