US 12,282,849 B2
Method for training classification model, classification method, apparatus and device
Yaqing Wang, Beijing (CN); and Dejing Dou, Beijing (CN)
Assigned to Beijing Baidu Netcom Science Technology Co., Ltd., Beijing (CN)
Filed by Beijing Baidu Netcom Science Technology Co., Ltd., Beijing (CN)
Filed on Jun. 16, 2021, as Appl. No. 17/349,280.
Claims priority of application No. 202011595164.5 (CN), filed on Dec. 28, 2020.
Prior Publication US 2021/0312288 A1, Oct. 7, 2021
Int. Cl. G06N 3/04 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01)
CPC G06N 3/08 (2013.01) [G06N 3/045 (2023.01)] 20 Claims
OG exemplary drawing
 
1. A method for training a classification model, comprising:
acquiring behavior information of multiple users and personal basic information of the multiple users; wherein categories of at least part of users of the multiple users are known;
inputting the personal basic information of the multiple users into a classification model to be trained to obtain feature information of the multiple users and predicted categories of users with known categories;
determining a first loss according to the behavior information of the multiple users and the feature information of the multiple users;
determining a second loss according to the predicted categories of the users with the known categories and real categories of the users with the known categories;
determining an end-to-end loss of the classification model to be trained according to the first loss and the second loss; and
training the classification model to be trained with a goal of minimizing the end-to-end loss to obtain a trained classification model; wherein in a training process, the feature information of the multiple users is updated by using the behavior information of the multiple users.