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Research PaperResearchia:202605.09002

Inductive Venn-Abers and related regressors

Ivan Petej

Abstract

Venn-Abers predictors are probabilistic predictors that enjoy appealing properties of validity, but their major limitation is that they are applicable only to the case of binary classification, with a recent extension to bounded regression. We generalize them to the case of unbounded regression, which requires adding an element of conformal prediction. In our simulation and empirical studies we investigate the predictive efficiency of point regressors derived from Venn-Abers regressors and argue...

Submitted: May 9, 2026Subjects: Machine Learning; Data Science

Description / Details

Venn-Abers predictors are probabilistic predictors that enjoy appealing properties of validity, but their major limitation is that they are applicable only to the case of binary classification, with a recent extension to bounded regression. We generalize them to the case of unbounded regression, which requires adding an element of conformal prediction. In our simulation and empirical studies we investigate the predictive efficiency of point regressors derived from Venn-Abers regressors and argue that they somewhat improve the predictive efficiency of standard regressors for larger training sets.


Source: arXiv:2605.06646v1 - http://arxiv.org/abs/2605.06646v1 PDF: https://arxiv.org/pdf/2605.06646v1 Original Link: http://arxiv.org/abs/2605.06646v1

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Submission Info
Date:
May 9, 2026
Topic:
Data Science
Area:
Machine Learning
Comments:
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