公开(公告)号：US20230351241A1

公开(公告)日：2023-11-02

申请号：US17639653

申请日：2021-04-12

Applicant: Beijing Baidu Netcom Science and Technology Co., Ltd.

Inventor： Huihui He ,  Leyi Wang ,  Minghao Liu ,  Jiangliang Guo

IPC: G06N20/00 ,  G06N7/01

CPC classification number: G06N20/00 ,  G06N7/01

Abstract: The present application discloses a model training method, a short message auditing method and apparatuses, a device, and a storage medium, and relates to the field of artificial intelligence. A specific implementation solution of model training is: performing a sample reduction on first unlabeled samples to obtain second unlabeled samples; inputting the second unlabeled samples to a machine learning model for prediction, to obtain a probability corresponding to a result of predicting the second unlabeled samples; selecting a third unlabeled sample from the second unlabeled samples according to the probability; and training the machine learning model by using a third unlabeled sample after labeling. In embodiments of the present application, redundant samples are removed through a sample reduction, such that the selected samples have a certain degree of representativeness. In addition, a machine learning model is used to further select an informative sample with the most labeling significance for the current model by using an active learning technology, the cost of labeling is reduced.