Uncertainty Quantification in Regression Neural Networks Using Likelihood-Based Belief Functions.
Thierry DenoeuxPublished in: BELIEF (2024)
Keyphrases
- belief functions
- neural network
- dempster shafer
- dempster shafer theory
- probability theory
- handling uncertainty
- uncertain information
- probability function
- regression model
- uncertain reasoning
- model selection
- combination rule
- markov tree
- maximum likelihood
- evidential reasoning
- pattern recognition
- back propagation
- artificial neural networks
- probability functions
- fuzzy numbers
- set valued
- probability measures
- genetic algorithm
- distributive lattices
- knowledge base
- machine learning