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Step-by-Step Data Quality Augmentation, Bias Mitigation, and Implementing Fairness Metrics using Synthetic data

Name: Step-by-Step Data Quality Augmentation, Bias Mitigation, and Implementing Fairness Metrics using Synthetic data
Keywords: Synthetic data, fairness metrics, data quality, bias mitigation

appsOther research productkeyboard_double_arrow_right Other ORP type 31 Oct 2022Publisher:Zenodo

Authors: Kurapati, Shalini; Gilli, Luca;

doi: 10.5281/zenodo.7266913 , 10.5281/zenodo.7266912

Step-by-Step Data Quality Augmentation, Bias Mitigation, and Implementing Fairness Metrics using Synthetic data

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Abstract

The aim of this report is to explain the functionalities of the software modules related to the deliverable on bias mitigation and fairness metrics of the TIME project, the successful WomenTechEU submission of Clearbox AI. The open source work done during the span of the project can be found in the following repositories: Structured Data Profiling library of Clearbox AI: https://github.com/Clearbox-AI/StructuredDataProfiling Bias Mitigation and Fairness module of Clearbox AI: https://github.com/Clearbox-AI/Bias-Detection-Mitigation

Keywords

Synthetic data, fairness metrics, data quality, bias mitigation

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