Abstract
In many supervised learning applications, the existence of additional information in training data is very common. Recently, Vapnik introduced a new method called LUPI which provides a learning paradigm under privileged (or additional) information. It describes the SVM+ technique to process this information in batch mode. Following this method, we apply the approach to deal with additional information by conformal predictors. An application to a medical diagnostic problem is considered and the results are reported.
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Yang, M., Nouretdinov, I., Luo, Z. (2013). Learning by Conformal Predictors with Additional Information. In: Papadopoulos, H., Andreou, A.S., Iliadis, L., Maglogiannis, I. (eds) Artificial Intelligence Applications and Innovations. AIAI 2013. IFIP Advances in Information and Communication Technology, vol 412. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41142-7_40
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DOI: https://doi.org/10.1007/978-3-642-41142-7_40
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