Marie-Hélène Masson

TL;DR: This paper proposes to characterize the probabilities of the different classes by simultaneous confidence intervals with a given confidence level [email protected] from this imprecise specification, a procedure for constructing a possibility distribution is described, insuring that the resulting possibility distribution will dominate the true probability distribution in at least 100% of the cases.

TL;DR: Nonparametric rank-based statistics depending only on linear orderings of the observations are extended to fuzzy data, leading to the concepts of fuzzy p-value, and graded rejection of the null hypothesis at a given significance level.

TL;DR: This method is extended to the case where dissimilarities are only known to lie within certain intervals, and shows the ability of this method to represent both the structure and the precision of dissimilarity measurements.

TL;DR: This paper describes an extension of principal component analysis allowing the extraction of a limited number of relevant features from high-dimensional fuzzy data, and the concept of correlation coefficient is extended to fuzzy numbers, allowing the interpretation of the new features in terms of the original variables.

TL;DR: This paper extendsMultidimensional scaling to the case where dissimilarities are expressed as intervals or fuzzy numbers, and each object is no longer represented by a point but by a crisp or a fuzzy region.