Uncertainty quantification in logistic regression using random fuzzy sets and belief functions

Cites Work

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Evidential calibration of binary SVM classifiers
Prediction of future observations using belief functions: a likelihood-based approach
40 years of Dempster-Shafer theory
Upper and lower probabilities induced by a fuzzy random variable
Bayesian computation for logistic regression
Possibility theory and statistical reasoning
Fuzzy sets as a basis for a theory of possibility
The concept of a linguistic variable and its application to approximate reasoning. I
The transferable belief model
Statistical inference in science
Learning monotone nonlinear models using the Choquet integral
Lymphoma segmentation from 3D PET-CT images using a deep evidential network
Fast semi-supervised evidential clustering
The Dempster-Shafer calculus for statisticians
A new evidential \(K\)-nearest neighbor rule based on contextual discounting with partially supervised learning
Evidential joint calibration of binary SVM classifiers
Decision-making with belief functions: a review
Parametric classification with soft labels using the evidential EM algorithm: linear discriminant analysis versus logistic regression
Forecasting using belief functions: an application to marketing econometrics
On the plausibility transformation method for translating belief function models to probability models
Likelihood-based belief function: justification and some extensions to low-quality data
The large-sample distribution of the likelihood ratio for testing composite hypotheses.
Possibility theory, probability and fuzzy sets. Misunderstandings, bridges and gaps
Advances in large-margin classifiers
Applied Logistic Regression
Inferential Models
Fuzzy sets
Upper and Lower Probabilities Induced by a Multivalued Mapping
New Methods for Reasoning Towards Posterior Distributions Based on Sample Data
A Gibbs Sampler for a Class of Random Convex Polytopes
Possibility-theoretic statistical inference offers performance and probativeness assurances
Belief functions induced by random fuzzy sets: a general framework for representing uncertain and fuzzy evidence
Reasoning with fuzzy and uncertain evidence using epistemic random fuzzy sets: general framework and practical models
NN-EVCLUS: neural network-based evidential clustering
The Elements of Statistical Learning
Representations of uncertainty in artificial intelligence: probability and possibility
Representations of uncertainty in AI: beyond probability and possibility