公开(公告)号：US20230394282A1

公开(公告)日：2023-12-07

申请号：US18454795

申请日：2023-08-24

申请人： DONGGUAN UNIVERSITY OF TECHNOLOGY

发明人： YI WANG ,  BO HUANG ,  ZHIWEI KE

IPC分类号： G06N3/045 ,  G06N3/094

CPC分类号： G06N3/045 ,  G06N3/094

摘要： A method for training an ensemble model based on feature diversified learning includes: acquiring a high-level feature vector of each of the base networks by inputting example data into a current ensemble model; determining an activation intensity interval; acquiring an update of diversified features of the current ensemble model; outputting an output result corresponding to the example data based on the updated diversified features of the current ensemble model; and acquiring a target ensemble model by calculating a target loss function of the current ensemble model based on the example data and the output result, adjusting parameter values of the current ensemble model, and inputting the example data into the current ensemble model with the adjusted parameter values to continue training until the target loss function converges.