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Audit Machine Learning Models Against Bias

机译:审核偏见的机器学习模型

摘要

A method and system of mitigating bias in a decision-making system are provided. A presence of bias is identified in one or more machine learning models. For each of the machine learning models, a presence of bias in an output of the model is determined. One or more options to mitigate a system bias during a processing stage, based on the identified presence of bias for each of the one or more models, are determined. One or more options to mitigate the system bias during a post-processing stage, based on the identified presence of bias in each output of the models, are determined. A combination of options is provided, including (i) a processing option for the processing stage, and (ii) a post-processing option for the post-processing stage, wherein the combination of options accommodates a threshold bias limit to the system bias and a total bias mitigation cost threshold.
机译:提供了一种减轻决策系统中的偏差的方法和系统。在一个或多个机器学习模型中识别出偏差的存在。对于每个机器学习模型,确定模型输出中存在偏差。基于针对一个或多个模型中的每一个所识别出的偏差的存在,来确定在处理阶段减轻系统偏差的一个或多个选项。基于在模型的每个输出中识别出的偏差的存在,确定减轻后处理阶段的系统偏差的一个或多个选项。提供选项的组合,包括(i)用于处理阶段的处理选项,和(ii)用于后处理阶段的后处理选项,其中选项的组合适应系统偏差的阈值偏差极限,以及总缓解偏差成本阈值。

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