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Simultaneous Improvement of ML Model Fairness and Performance by Identifying Bias in Data
Machine learning models built on datasets containing discriminative instances attributed to various underlying factors result in biased and unfair outcomes.
MLSmellHound: A Context-Aware Code Analysis Tool
In our approach we attempt to resolve this problem by exploring the use of context which includes i) purpose of the source code, ii) technical domain, iii) problem domain, iv) team norms, v) operational environment, and vi) development lifecycle stage to provide contextualised error reporting for code analysis.
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