Taillandier P. auteur aut IRD Drogoul Alexis auteur aut IRD text bookSection eng text/pdf born digital access Nowadays, supervised learning is commonly used in many domains. Indeed, many works propose to learn new knowledge from examples that translate the expected behaviour of the considered system. A key issue of supervised learning concerns the description language used to represent the examples. In this paper, we propose a method to evaluate the feature set used to describe them. Our method is based on the computation of the consistency of the example base. We carried out a case study in the domain of geomatic in order to evaluate the sets of measures used to characterise geographic objects. The case study shows that our method allows to give relevant evaluations of measure sets specialized INTELLIGENCE ARTIFICIELLE SYSTEME D'INFORMATION GEOGRAPHIQUE GEOMATIQUE COHERENCE 122INTAR Son Bao Pham ed. edt IRD Tuan-Hao Hoang ed. edt IRD McKay B. ed. edt IRD Hirota K. ed. edt IRD 63-68 New York IEEE 2010 KSE 2010.International Conference on Knowledge and Systems Engineering, 2., Hanoi (VNM), 2010/10/07-09 https://www.documentation.ird.fr/hor/fdi:010055254 10.1109/KSE.2010.28 978-1-4244-8334-1 [F B010055254] https://www.documentation.ird.fr/hor/fdi:010055254 https://www.documentation.ird.fr/intranet/publi/2023-02/010055254.pdf Accès réservé (Intranet de l'IRD) IRD - Base Horizon / Pleins textes 2012-05-07 2023-02-28 fdi:010055254 fre