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Found 2 papers, 1 papers with code
Model-agnostic and Scalable Counterfactual Explanations via Reinforcement Learning
Counterfactual instances are a powerful tool to obtain valuable insights into automated decision processes, describing the necessary minimal changes in the input space to alter the prediction towards a desired target.
Preservation of Anomalous Subgroups On Machine Learning Transformed Data
Our evaluation confirmed that the approach was able to produce synthetic datasets that preserved a high level of subgroup differentiation as identified initially in the original dataset.
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