Entropy Reweighted Conformal Classification
<|reference_start|>Entropy Reweighted Conformal Classification: Conformal Prediction (CP) is a powerful framework for constructing prediction sets with guaranteed coverage. However, recent studies have shown that integrating confidence calibration with CP can lead to a degradation in efficiency. In this paper, We propose an adaptive approach that considers the classifier's uncertainty and employs entropy-based reweighting to enhance the efficiency of prediction sets for conformal classification. Our experimental results demonstrate that this method significantly improves efficiency.<|reference_end|>
@article{luo2024entropy,
    title={Entropy Reweighted Conformal Classification},
    author={Rui Luo and Nicolo Colombo},
    journal={arXiv preprint arXiv:2407.17377},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.17377},
    primaryClass={cs.LG}
}