IEEE Computational Intelligence Magazine - November 2022 - 69

classifiers for the decomposed binary
sub-problems. It balances the precision
and recall of different classes adaptively.
In this work, TPR and FPR was
adopted as two objectives. In the future,
precision and recall are planned to be
used as the optimized objectives for
designing new MOEAs for the decomposition-based
multiclass classification.
Acknowledgment
This work was supported in part by
the National Natural Science Foundation
of China under Grants 62076001,
61822301, 61672033, 61976001,
61876166, 61663046, and U1804262
and in part by the University Synergy
Innovation Program of Anhui Province
under Grant GXXT-2020-050.
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NOVEMBER 2022 | IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE 69
http://dx.doi.org/10.1109/TCYB.2020.3042243 http://dx.doi.org/10.1109/TEVC.2021.3100056 http://dx.doi.org/10.1109/TEVC.2021.3100056 http://dx.doi.org/10.1109/TCYB.2021.3065340 http://dx.doi.org/10.1109/TCYB.2021.3090769
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