CPC G06N 20/00 (2019.01) | 20 Claims |
1. A method, comprising:
receiving an input dataset;
generating an anonymized reconstructed dataset based at least on the input dataset wherein the generated dataset includes tabular data;
introducing a predetermined bias into the generated dataset while training a generative adversarial network (GAN) model, wherein:
the generative adversarial network model is configured to append one or more columns to the generated dataset, the one or more columns including at least one dataset attribute or attribute of interest for fairness evaluation; and
a generative adversarial network sampler is configured to randomly sample the generated dataset appended with the one or more columns;
forming an evaluation dataset based at least on the generated dataset with the predetermined bias; and
outputting the evaluation dataset for evaluating algorithmic fairness.
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