User feature optimization method and device in user feature group, medium and electronic equipment

Abstract

The invention relates to a user feature optimization method and device in a user feature group, a medium and electronic equipment, and belongs to the technical field of machine learning application, and the method comprises the steps: initializing and generating a plurality of user feature combinations; inputting each user feature combination and the optimization target into a first machine learning model to obtain an evaluation score; obtaining a plurality of user feature combinations in a first score range and a plurality of user feature combinations in a second score range; obtaining a userfeature difference between the user feature combination of each first score range and the user feature combination of the second score range; inputting the plurality of user feature differences and the optimization target into a second machine learning model to obtain a prediction optimization user feature combination; and obtaining a target optimization user feature combination. According to theinvention, the user feature combination corresponding to the optimization target is predicted through the machine learning model according to the distinguishing features of part of the user feature combinations, so that the high efficiency and accuracy of obtaining the target user feature combination are ensured.

Description

technical field [0001] The present disclosure relates to the technical field of machine learning applications, and in particular, to a method, device, medium, and electronic device for optimizing user characteristics in user characteristic groups. Background technique [0002] The optimization of user characteristics in user characteristic groups is to find the combination of user characteristics for special purposes that meet the needs from the user characteristic groups with a large number of user characteristics, that is, to find optimized user characteristics from the user characteristic groups. For example, search for a combination of user characteristics that meet the requirements from user characteristics and user characteristic groups, in order to obtain a group of user combinations that can meet the predetermined purpose. [0003] At present, the optimization of user features in the user feature group is mainly by crawling keywords from the user feature group, setti...

AI Technical Summary

Problems solved by technology

In this way, in the process of user feature optimization, the difference between user features in all user feature groups cannot be considered, and the combination of user features obtained has the problem of unreasonable combination, and the process of obtaining user feature combinations requires a large amount of data. statistics, the algorithm load is heavy, and the acquisition efficiency is low

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