Browsing by Author Serrurier, M

Showing results 1 to 18 of 18
Issue DateTitleAuthor(s)
7-Nov-2016Analogy in recommendation. Numerical vs. Ordinal: A discussionHug, N; Prade, H; Richard, G; Serrurier, M
1-Jan-2016Analogical classifiers: A theoretical perspectiveHug, N; Prade, H; Richard, G; Serrurier, M
1-Jan-2015Entropy evaluation based on confidence intervals of frequency estimates: Application to the learning of decision treesSerrurier, M; Prade, H
16-Mar-2014Naive possibilistic classifiers for imprecise or uncertain numerical dataBounhas, M; Ghasemi Hamed, M; Prade, H; Serrurier, M; Mellouli, K
9-Oct-2013A scalable learning algorithm for kernel probabilistic classifierSerrurier, M; Prade, H
1-Sep-2013An informational distance for estimating the faithfulness of a possibility distribution, viewed as a family of probability distributions, with respect to dataSerrurier, M; Prade, H
1-Jan-2013Possibilistic classifiers for numerical dataBounhas, M; Mellouli, K; Prade, H; Serrurier, M
5-Nov-2012Classification based on possibilistic likelihoodSerrurier, M; Prade, H
2-Nov-2012A possibilistic rule-based classifierBounhas, M; Prade, H; Serrurier, M; Mellouli, K
19-Oct-2011Imprecise regression based on possibilistic likelihoodSerrurier, M; Prade, H
27-Sep-2011Maximum-likelihood principle for possibility distributions viewed as families of probabilitiesSerrurier, M; Prade, H
14-Jul-2011Possibilistic classifiers for uncertain numerical dataBounhas, M; Prade, H; Serrurier, M; Mellouli, K
1-Dec-2010Why imprecise regression: A discussionPrade, H; Serrurier, M
25-Oct-2010From Bayesian classifiers to possibilistic classifiers for numerical dataBounhas, M; Mellouli, K; Prade, H; Serrurier, M
16-Oct-2009Elicitation of sugeno integrals: A version space learning perspectivePrade, H; Rico, A; Serrurier, M
27-Aug-2009Elicitating sugeno integrals: Methodology and a case studyPrade, H; Rico, A; Serrurier, M; Raufaste, E
1-Oct-2008Bipolar version space learningPrade, H; Serrurier, M
15-Mar-2008Improving inductive logic programming by using simulated annealingSerrurier, M; Prade, H