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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Applying Conformal Prediction to the Bovine TB Diagnosing
verfasst von : Dmitry Adamskiy, Ilia Nouretdinov, Andy Mitchell, Nick Coldham, Alex Gammerman
Erschienen in: Artificial Intelligence Applications and Innovations
Verlag: Springer Berlin Heidelberg
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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.