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Representing Uncertainty by Possibility Distributions Encoding Confidence Bands, Tolerance and Prediction Intervals., , and . SUM, volume 7520 of Lecture Notes in Computer Science, page 233-246. Springer, (2012)From Bayesian Classifiers to Possibilistic Classifiers for Numerical Data., , , and . SUM, volume 6379 of Lecture Notes in Computer Science, page 112-125. Springer, (2010)CYNTHIA: An HTML Browser for Visually Handicapped People., and . ICCHP, volume 2398 of Lecture Notes in Computer Science, page 353-359. Springer, (2002)Learning Structure of Bayesian Networks by Using Possibilistic Upper Entropy., and . SMPS, volume 315 of Advances in Intelligent Systems and Computing, page 87-95. Springer, (2014)Enriching Relational Learning with Fuzzy Predicates., , and . PKDD, volume 2838 of Lecture Notes in Computer Science, page 399-410. Springer, (2003)Getting adaptability or expressivity in inductive logic programming by using fuzzy predicates., and . FUZZ-IEEE, page 73-77. IEEE, (2004)Fuzzy Inductive Logic Programming: Learning Fuzzy Rules with their Implication., , , and . FUZZ-IEEE, page 613-618. IEEE, (2005)Improving inductive logic programming by using simulated annealing., and . Inf. Sci., 178 (6): 1423-1441 (2008)Naive possibilistic classifiers for imprecise or uncertain numerical data., , , , and . Fuzzy Sets and Systems, (2014)Bipolar version space learning., and . Int. J. Intell. Syst., 23 (10): 1135-1152 (2008)