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Conference Papers Year : 2011

Applying Conformal Prediction to the Bovine TB Diagnosing

Dmitry Adamskiy
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Ilia Nouretdinov
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Nick Coldham
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Alex Gammerman
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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.
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Dates and versions

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





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⟩
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