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pro vyhledávání: '"Pramote Sittijuk"'
Autor:
Pramote Sittijuk, Kreangsak Tamee
Publikováno v:
Symmetry, Vol 16, Iss 9, p 1181 (2024)
We introduce the random high-local performance client selection strategy, termed Fed-RHLP. This approach allows opportunities for higher-performance clients to contribute more significantly by updating and sharing their local models for global aggreg
Externí odkaz:
https://doaj.org/article/5ce06f0f2d8b408bb1fae4b5e44e4be1
Autor:
Kriengsuk Tamee, Pramote Sittijuk
Publikováno v:
JCSSE
AI often suffers from getting imbalanced data distribution as unequal samples in classes which will increase the bias of machine learning algorithms. This research aimed to study effects of skew data distribution towards development of data rebalanci