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Related Questions
- Can accuracy, F1-score, and AUC-ROC be used as metrics in domain adaptation to evaluate how well a model generalizes across different domains?
- In domain adaptation, how does accuracy relate to the similarity between source and target distributions?
- Can F1-score be used to compare the performance of different adaptation algorithms on a target dataset?
- How does AUC-ROC relate to class imbalance in domain adaptation scenarios?
- Can AUC-ROC be used as a metric to evaluate the effectiveness of domain adaptation when there are multiple classes in the target domain?
- What are some common metrics used in domain adaptation to evaluate the performance of adaptation techniques, and how do these metrics relate to accuracy?
- In domain adaptation, is F1-score a robust metric when dealing with categorical or continuous target variables, or does it favor numerical accuracy?
- Can model calibration metrics, such as Expected Calibration Error (ECE), be used in domain adaptation to evaluate how confident a model is in its predictions on the target dataset?
- How does the effectiveness of AUC-ROC depend on the proportion of each class in the source and target datasets,?
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