Probability-possibility transformations, triangular fuzzy sets, and probabilistic inequalities
A possibility measure can encode a family of probability measures. This fact is the basis for a
transformation of a probability distribution into a possibility distribution that generalises the …
transformation of a probability distribution into a possibility distribution that generalises the …
A systematic approach to the assessment of fuzzy association rules
In order to allow for the analysis of data sets including numerical attributes, several
generalizations of association rule mining based on fuzzy sets have been proposed in the …
generalizations of association rule mining based on fuzzy sets have been proposed in the …
Possibilistic classifiers for numerical data
M Bounhas, K Mellouli, H Prade, M Serrurier - Soft Computing, 2013 - Springer
Abstract Naive Bayesian Classifiers, which rely on independence hypotheses, together with
a normality assumption to estimate densities for numerical data, are known for their …
a normality assumption to estimate densities for numerical data, are known for their …
In defense of fuzzy association analysis
E Hullermeier, Y Yi - IEEE Transactions on Systems, Man, and …, 2007 - ieeexplore.ieee.org
This short correspondence is a reply to a recently published paper by Verlinde et al.(2006)
in which the authors empirically compared fuzzy and nonfuzzy association analysis and, on …
in which the authors empirically compared fuzzy and nonfuzzy association analysis and, on …
An informational distance for estimating the faithfulness of a possibility distribution, viewed as a family of probability distributions, with respect to data
M Serrurier, H Prade - International journal of approximate reasoning, 2013 - Elsevier
An acknowledged interpretation of possibility distributions in quantitative possibility theory is
in terms of families of probabilities that are upper and lower bounded by the associated …
in terms of families of probabilities that are upper and lower bounded by the associated …
Fuzzy histograms and density estimation
K Loquin, O Strauss - Soft methods for integrated uncertainty modelling, 2006 - Springer
The probability density function is a fundamental concept in statistics. Specifying the density
function f of a random variable X on Ω gives a natural description of the distribution of X on …
function f of a random variable X on Ω gives a natural description of the distribution of X on …
Histogram density estimators based upon a fuzzy partition
K Loquin, O Strauss - Statistics & Probability Letters, 2008 - Elsevier
This paper presents a density estimator based upon a histogram computed on a fuzzy
partition. We prove the consistency of this estimator in the Mean Squared Error (MSE). We …
partition. We prove the consistency of this estimator in the Mean Squared Error (MSE). We …
From bayesian classifiers to possibilistic classifiers for numerical data
M Bounhas, K Mellouli, H Prade, M Serrurier - … 4th International Conference …, 2010 - Springer
Naïve Bayesian classifiers are well-known for their simplicity and efficiency. They rely on
independence hypotheses, together with a normality assumption, which may be too …
independence hypotheses, together with a normality assumption, which may be too …
Quasi-continuous histograms
O Strauss - Fuzzy sets and systems, 2009 - Elsevier
Histograms are very useful for summarizing statistical information associated with a set of
observed data. They are one of the most frequently used density estimators due to their ease …
observed data. They are one of the most frequently used density estimators due to their ease …
Automatic background generation from a sequence of images based on robust mode estimation
In this paper, we present a novel method for generating a background model from a
sequence of images with moving objects. Our approach is based on non-parametric …
sequence of images with moving objects. Our approach is based on non-parametric …