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Modifications to p-Values of Conformal Predictors

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Statistical Learning and Data Sciences (SLDS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9047))

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Abstract

The original definition of a p-value in a conformal predictor can sometimes lead to too conservative prediction regions when the number of training or calibration examples is small. The situation can be improved by using a modification to define an approximate p-value. Two modified p-values are presented that converges to the original p-value as the number of training or calibration examples goes to infinity.

Numerical experiments empirically support the use of a p-value we call the interpolated p-value for conformal prediction. The interpolated p-value seems to be producing prediction sets that have an error rate which corresponds well to the prescribed significance level.

This work was supported by the Swedish Foundation for Strategic Research through the project High-Performance Data Mining for Drug Effect Detection (IIS11-0053) and the Knowledge Foundation through the project Big Data Analytics by Online Ensemble Learning (20120192).

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Correspondence to Lars Carlsson .

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Carlsson, L., Ahlberg, E., Boström, H., Johansson, U., Linusson, H. (2015). Modifications to p-Values of Conformal Predictors. In: Gammerman, A., Vovk, V., Papadopoulos, H. (eds) Statistical Learning and Data Sciences. SLDS 2015. Lecture Notes in Computer Science(), vol 9047. Springer, Cham. https://doi.org/10.1007/978-3-319-17091-6_20

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  • DOI: https://doi.org/10.1007/978-3-319-17091-6_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17090-9

  • Online ISBN: 978-3-319-17091-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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