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.
Harris Papadopoulos; Andreas S. Andreou; Lazaros Iliadis; Ilias Maglogiannis. 9th Artificial Intelligence Applications and Innovations (AIAI), Sep 2013, Paphos, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-412, pp.394-400, 2013, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-41142-7_40〉
https://hal.inria.fr/hal-01459634
Contributeur : Hal Ifip
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Soumis le : mardi 7 février 2017 - 13:05:50
Dernière modification le : vendredi 1 décembre 2017 - 01:16:34
Document(s) archivé(s) le : lundi 8 mai 2017 - 14:03:01
Meng Yang, Ilia Nouretdinov, Zhiyuan Luo. Learning by Conformal Predictors with Additional Information. Harris Papadopoulos; Andreas S. Andreou; Lazaros Iliadis; Ilias Maglogiannis. 9th Artificial Intelligence Applications and Innovations (AIAI), Sep 2013, Paphos, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-412, pp.394-400, 2013, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-41142-7_40〉. 〈hal-01459634〉
