Computer Science > Machine Learning
[Submitted on 24 Jul 2024]
Title:Entropy Reweighted Conformal Classification
View PDF HTML (experimental)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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