Feb 16, 2022 · The results show numerous bias and unfairness detection and mitigation approaches for ML technologies, with clearly defined metrics in the ...
This study examines the current knowledge on bias and unfairness in machine learning models. The systematic review followed the PRISMA guidelines.
Nov 3, 2022 · This study aims to examine the latest existing knowledge about bias and unfairness in machine learning (ML) models with the RSL methodology and ...
Feb 17, 2022 · This study aims to examine existing knowledge on bias and unfairness in Machine Learning models, identifying mitigation methods, fairness metrics, and ...
Jan 13, 2023 · This study examines the current knowledge on bias and unfairness in machine learning models. The systematic review followed the PRISMA guidelines.
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Dec 7, 2022 · One of the difficulties of artificial intelligence is to ensure that model decisions are fair and free of bias. In research, datasets, metrics, ...
This study examines the current knowledge on bias and unfairness in machine learning models. ... Monitoring bias and fairness in machine learning models: A review ...
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Bias and unfairness in machine learning models: A systematic review on datasets, tools, fairness metrics, and identification and mitigation methods. Big ...
Jan 31, 2024 · ML models can exhibit various unfairness issues, encompassing biases and discriminatory outcomes. Discussions often revolve around biases in ...
This systematic review seeks research on artificial intelligence that studies the unfair results produced by bias. The search queries are considered as a base ...