On the Use of Min-Based Revision Under Uncertain Evidence for Possibilistic Classifiers.
Salem BenferhatKarim TabiaPublished in: IFSA/EUSFLAT Conf. (2009)
Keyphrases
- possibility theory
- belief revision
- possibilistic networks
- decision trees
- incomplete information
- naive bayes
- linear classifiers
- empirical evidence
- support vector
- training data
- possibilistic logic
- machine learning algorithms
- training set
- test set
- supervised classification
- classification systems
- feature selection
- belief functions
- training samples
- belief change
- decision making
- classifier combination
- multiple classifiers
- combination rule
- classification rate
- classification models
- training examples
- feature set
- nonmonotonic reasoning
- knowledge base
- neural network