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.
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© 2011 IFIP International Federation for Information Processing
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Adamskiy, D., Nouretdinov, I., Mitchell, A., Coldham, N., Gammerman, A. (2011). Applying Conformal Prediction to the Bovine TB Diagnosing. In: Iliadis, L., Maglogiannis, I., Papadopoulos, H. (eds) Artificial Intelligence Applications and Innovations. EANN AIAI 2011 2011. IFIP Advances in Information and Communication Technology, vol 364. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23960-1_52
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DOI: https://doi.org/10.1007/978-3-642-23960-1_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23959-5
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