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FairML : ToolBox for diagnosing bias in predictive modeling · Study

ThesisFairML : ToolBox for diagnosing bias in predictive modeling

Julius Adebayo2016

Thesis2016

FairML : ToolBox for diagnosing bias in predictive modeling

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Ethics and Social Impacts of AI Explainable Artificial Intelligence (XAI)Imbalanced Data Classification Techniques

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2022Toward Involving End-users in Interactive Human-in-the-loop AI Fairness 2020LiFT 2020Bias and ethical considerations in machine learning and the automation of perioperative risk assessment 2022Dbias: detecting biases and ensuring fairness in news articles 2021Better Reporting of Studies on Artificial Intelligence: CONSORT-AI and Beyond 2023A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithms 2020Towards Formal Fairness in Machine Learning 2021Towards Ethical Data-Driven Software: Filling the Gaps in Ethics Research & Practice

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Year2016

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Published2016-01-01

Languageen

Citations70

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ShelfEthics and Social Impacts of AI

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openalex_workW2609237802

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