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Found 3 papers, 2 papers with code
From Uncertainty to Precision: Enhancing Binary Classifier Performance through Calibration
The assessment of binary classifier performance traditionally centers on discriminative ability using metrics, such as accuracy.
Optimal Transport for Counterfactual Estimation: A Method for Causal Inference
Here, we will have the dual view: doing an intervention, or changing the treatment (even just hypothetically, in a thought experiment, for example by asking what would have happened if a person had been Black) can have an impact on the values of x.
GAM(L)A: An econometric model for interpretable Machine Learning
Moreover, the results also suggest that the performance of GAM(L)A is not significantly different from that of random forest and gradient boosting.
BIG-bench Machine Learning
Interpretable Machine Learning
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