Aggregated Conformal Prediction - Artificial Intelligence Applications and Innovations (AIAI 2014 - Workshops:CoPA,MHDW, IIVC, and MT4BD) Access content directly
Conference Papers Year : 2014

Aggregated Conformal Prediction

Lars Carlsson
  • Function : Author
  • PersonId : 992367
Martin Eklund
  • Function : Author
  • PersonId : 992368
Ulf Norinder
  • Function : Author
  • PersonId : 992369

Abstract

We present the aggregated conformal predictor (ACP), an extension to the traditional inductive conformal prediction (ICP) where several inductive conformal predictors are applied on the same training set and their individual predictions are aggregated to form a single prediction on an example. The results from applying ACP on two pharmaceutical data sets (CDK5 and GNRHR) indicate that the ACP has advantages over traditional ICP. ACP reduces the variance of the prediction region estimates and improves efficiency. Still, it is more conservative in terms of validity than ICP, indicating that there is room for further improvement of efficiency without compromising validity.
Fichier principal
Vignette du fichier
978-3-662-44722-2_25_Chapter.pdf (260.72 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01391050 , version 1 (02-11-2016)

Licence

Attribution

Identifiers

Cite

Lars Carlsson, Martin Eklund, Ulf Norinder. Aggregated Conformal Prediction. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. pp.231-240, ⟨10.1007/978-3-662-44722-2_25⟩. ⟨hal-01391050⟩
75 View
814 Download

Altmetric

Share

Gmail Facebook X LinkedIn More