Maximizing diversity by transformed ensemble learning

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Shasha Mao, Jiawei Chen, Licheng Jiao, Shuiping Gou, Rongfang Wang

Published: 2019, Last Modified: 01 Oct 2024Appl. Soft Comput. 2019EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•A novel ensemble learning is proposed to balance diversity and individual accuracy.•The whole process can be implemented as the linear transforms of individuals.•The derived objective function can be efficiently solved by an ADMM-like algorithm.