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On the Use of m-Probability-Estimation and Imprecise Probabilities in the Naïve Bayes Classifier., , , and . Int. J. Uncertain. Fuzziness Knowl. Based Syst., 28 (4): 661-682 (2020)Combination in the theory of evidence via a new measurement of the conflict between evidences., , and . Expert Syst. Appl., (2021)Using extreme prior probabilities on the Naive Credal Classifier., , , and . Knowl. Based Syst., (2022)MPE Computation in Bayesian Networks Using Mini-Bucket and Probability Trees Approximation., , , and . Int. J. Uncertain. Fuzziness Knowl. Based Syst., 28 (5): 785-805 (2020)Improving the Results in Credit Scoring by Increasing Diversity in Ensembles of Classifiers., and . IEEE Access, (2023)Using Credal C4.5 for Calibrated Label Ranking in Multi-Label Classification., , , and . ISIPTA, volume 147 of Proceedings of Machine Learning Research, page 220-228. PMLR, (2021)Bagging of credal decision trees for imprecise classification., , , , and . Expert Syst. Appl., (2020)A cost-sensitive Imprecise Credal Decision Tree based on Nonparametric Predictive Inference., , , and . Appl. Soft Comput., (2022)Uncertainty-based information measures on the approximate non-parametric predictive inference model., and . Int. J. Gen. Syst., 50 (2): 159-181 (2021)A Variation of the Algorithm to Achieve the Maximum Entropy for Belief Functions., , and . Entropy, 25 (6): 867 (June 2023)