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arXiv · 2407.17377

Entropy Reweighted Conformal Classification

Rui Luo·Nicolo Colombo
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Abstract

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.

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Rui Luo, Nicolo Colombo. 2024-07-24. Entropy Reweighted Conformal Classification. https://arxiv.org/abs/2407.17377

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