No evaluation without fair representation : Impact of label and selection bias on the evaluation, performance and mitigation of classification models

No evaluation without fair representation : Impact of label and selection bias on the evaluation, performance and mitigation of classification models explores A framework for analyzing and mitigating bias in machine learning classification models to enhance fairness and accuracy.. Commercial viability score: 3/10 in Fairness in Machine Learning.