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Optimized conformal classification using gradient descent approximation · Around

2021

Optimized conformal classification using gradient descent approximation

Bellotti, Anthony

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Understand

Conformal predictors are an important class of algorithms that allow predictions to be made with a user-defined confidence level.

They are able to do this by outputting prediction sets, rather than simple point predictions.
The conformal predictor is valid in the sense that the accuracy of its predictions is guaranteed to meet the confidence level, only assuming exchangeability in the data.
Since accuracy is guaranteed, the performance of a conformal predictor is measured through the efficiency of the prediction sets.

Built on

Algorithmic learning in a random world
Vladimir Vovk, Alexander Gammerman, and Glenn Shafer · 2005
Earlier work this paper cites.
UCI Machine Learning Repository
A Frank and A Asuncion · 2010
Earlier work this paper cites.
Machine learning classification with confidence: Application of transductive conformal predictors to mri-based diagnostic and prognostic markers in depression
Ilia Nouretdinov, Sergi G. Costafreda, Alexander Gammerman, Alexey Chervonenkis, Vladimir Vovk, Vladimir Vapnik, and Cynthia H.Y. Fu · 2010
Earlier work this paper cites.
Biomedical applications: Diagnostics and prognostics
IR Nouretdinov, A Bellotti, and A Gammerman · 2014
Earlier work this paper cites.

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Then

Discrimination of different species of dendrobium with an electronic nose using aggregated conformal predictor
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Later among the works it cites.
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A Bellotti · 2020
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N Colombo and V Vovk · 2020
Later among the works it cites.

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