Modifications of Conformal Predictors

Vladimir Vovk, Alexander Gammerman and Glenn Shafer
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Vladimir Vovk: University of London, Royal Holloway
Alexander Gammerman: University of London, Royal Holloway
Glenn Shafer: Rutgers University

Chapter Chapter 4 in Algorithmic Learning in a Random World, 2022, pp 107-142 from Springer

Abstract: Abstract So far we have emphasized desirable properties of conformal predictors (also known as full conformal predictors): validity, asymptotic efficiency, and flexibility (ability to incorporate a wide range of machine-learning methods); we have also mentioned that the hedged predictions output by good conformal predictors are “conditional”, in the sense that they take full account of the object to be predicted. In this chapter we will discuss some limitations of full conformal prediction, starting from their relative computational inefficiency, and ways to overcome or alleviate these limitations.

Keywords: Inductive conformal prediction; Inductive conformity measure; Cross-conformal prediction; Transductive conformal prediction; Conditionality; Mondrian prediction (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-06649-8_4

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DOI: 10.1007/978-3-031-06649-8_4

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