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Refactor roc_curve_by_attr to use one thresholds for all the sensitive attribute values
If different sensitive attribute values use different thresholds, the equalized odds intervention won't be sync across the values.
Therefore, an updated version of roc_curve from sklearn should be used, that takes the global thresholds and generate (fpr,tpr) for each sensitive attribute value:
https://github.com/scikit-learn/scikit-learn/blob/7b136e92acf49d46251479b75c88cba632de1937/sklearn/metrics/ranking.py#L535