The content discusses the importance of prediction set sizes in conformal predictors and proposes methods to estimate the expected size. Theoretical quantification and practical estimation procedures are detailed, with experiments validating the efficacy of the proposed approaches.
While conformal predictors offer error guarantees, the size of prediction sets is crucial for practical use. The authors quantify expected set sizes theoretically and propose empirical estimation methods. These procedures aim to provide accurate insights without requiring multiple data collections.
The study focuses on split conformal prediction frameworks and their expected set sizes. By deriving point estimates and interval bounds, the authors offer a practical approach to characterize prediction set sizes. Experiments on real-world datasets validate the effectiveness of their results.
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by Guneet S. Dh... at arxiv.org 03-12-2024
https://arxiv.org/pdf/2306.07254.pdfDeeper Inquiries