Applying Conformal Prediction to the Bovine TB Diagnosing - Artificial Intelligence Applications and Innovations - Part II Access content directly
Conference Papers Year : 2011

Applying Conformal Prediction to the Bovine TB Diagnosing

Dmitry Adamskiy
  • Function : Author
  • PersonId : 1014218
Ilia Nouretdinov
  • Function : Author
  • PersonId : 992376
Nick Coldham
  • Function : Author
  • PersonId : 1014220
Alex Gammerman
  • Function : Author
  • PersonId : 992379

Abstract

Conformal prediction is a recently developed flexible method which allows making valid predictions based on almost any underlying classification or regression algorithm. In this paper, conformal prediction technique is applied to the problem of diagnosing Bovine Tuberculosis. Specifically, we apply Nearest-Neighbours Conformal Predictor to the VETNET database in an attempt to allow the increase of the positive prediction rate of the existing Skin Test. Conformal prediction framework allows us to do so while controlling the risk of misclassifying true positives.
Fichier principal
Vignette du fichier
978-3-642-23960-1_52_Chapter.pdf (123.71 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01571484 , version 1 (02-08-2017)

Licence

Attribution

Identifiers

Cite

Dmitry Adamskiy, Ilia Nouretdinov, Andy Mitchell, Nick Coldham, Alex Gammerman. Applying Conformal Prediction to the Bovine TB Diagnosing. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. pp.449-454, ⟨10.1007/978-3-642-23960-1_52⟩. ⟨hal-01571484⟩
96 View
81 Download

Altmetric

Share

Gmail Facebook X LinkedIn More