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Parameter-Free Bayesian Decision Trees for Uplift Modeling., , and . PAKDD (2), volume 13936 of Lecture Notes in Computer Science, page 309-321. Springer, (2023)Evaluation de l'uplift sur des données biaisées dans le cas du Non-Random Assignment., , and . EGC, volume E-38 of RNTI, page 51-62. Editions RNTI, (2022)Contact personalization using a score understanding method., , and . IJCNN, page 649-654. IEEE, (2008)Une approche bayésienne non paramétrique de sélection de variables pour la modélisation de l'uplift., , , and . EGC, volume E-39 of RNTI, page 523-530. Editions RNTI, (2023)Feedback - Study and Improvement of the Random Forest of the Mahout library in the context of marketing data of Orange., , , and . EGC, volume E-28 of Revue des Nouvelles Technologies de l'Information, page 413-424. Hermann-Éditions, (2015)Apprentissage fédératif pour la prédiction du churn : une évaluation., , , and . EGC, volume E-35 of RNTI, page 141-152. Éditions RNTI, (2019)A Bayes Evaluation Criterion for Decision Trees., , and . EGC (best of volume), volume 292 of Studies in Computational Intelligence, page 21-38. Springer, (2009)Un critère d'évaluation Bayésienne pour la construction d'arbre de décision., , and . EGC, volume RNTI-E-15 of Revue des Nouvelles Technologies de l'Information, page 67-78. Cépaduès-Éditions, (2009)Sélection et transformation de variables pour la classification Multi-Label par une approche MDL., , and . EGC, volume E-33 of Revue des Nouvelles Technologies de l'Information, page 345-350. Éditions RNTI, (2017)A Non-parametric Bayesian Approach for Uplift Discretization and Feature Selection., , , and . ECML/PKDD (5), volume 13717 of Lecture Notes in Computer Science, page 239-254. Springer, (2022)