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Diversity Analysis on Boosting Nominal Concepts.

, , and . PAKDD (1), volume 7301 of Lecture Notes in Computer Science, page 306-317. Springer, (2012)

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Catégorisation des méthodes de classification fondées sur l'Analyse de Concepts Formels., , and . IC, page 159-162. (2020)A New Feature Selection Method for Nominal Classifier based on Formal Concept Analysis., , and . KES, volume 112 of Procedia Computer Science, page 186-194. Elsevier, (2017)Cloud Implementation of Classier Nominal Concepts using DistributedWekaSpark., , and . ICFCA (Supplements), volume 2378 of CEUR Workshop Proceedings, page 125-136. CEUR-WS.org, (2019)Boosting Formal Concepts to Discover Classification Rules., and . IEA/AIE, volume 5579 of Lecture Notes in Computer Science, page 501-510. Springer, (2009)Adaptive Learning of Nominal Concepts for Supervised Classification., and . KES (1), volume 6276 of Lecture Notes in Computer Science, page 121-130. Springer, (2010)Vers un critère d'arrêt de Boosting basé sur la diversité des classifieurs., , and . INFORSID, page 111-126. (2011)Apprentissage supervisé adaptatif de Concepts Formels à partir des données nominales., and . EGC, volume RNTI-E-19 of Revue des Nouvelles Technologies de l'Information, page 649-650. Cépaduès-Éditions, (2010)Parallel Learning and Classification for Rules based on Formal Concepts., , and . KES, volume 35 of Procedia Computer Science, page 358-367. Elsevier, (2014)Générer des règles de classification par dopage de concepts formels., and . EGC, volume RNTI-E-15 of Revue des Nouvelles Technologies de l'Information, page 181-186. Cépaduès-Éditions, (2009)DFC: A Performant Dagging Approach of Classification Based on Formal Concept., , and . Int. J. Artif. Intell. Mach. Learn., 11 (2): 38-62 (2021)