Classifier uncertainty: evidence, potential impact, and probabilistic treatment.
Niklas TötschDaniel HoffmannPublished in: CoRR (2020)
Keyphrases
- potential impact
- uncertain data
- belief functions
- probability theory
- combination rule
- handling uncertainty
- evidence theory
- feature space
- dempster shafer
- conditional probabilities
- decision theory
- empirical evidence
- probabilistic model
- decision trees
- evidential reasoning
- dempster shafer theory
- classification algorithm
- training examples
- bayesian networks
- training data
- bayes rule
- classifier systems
- probabilistic logic
- imprecise probabilities
- probability measures
- knowledge about the world
- classification process
- svm classifier
- learning algorithm
- feature selection
- support vector
- training set
- generative model
- linear classifiers
- neural network
- machine learning
- probabilistic knowledge
- training samples
- nearest neighbor classifier
- classification method
- classification scheme
- decision making
- class labels
- data sets