Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures?
Lisa WimmerYusuf SalePaul HofmanBernd BischlEyke HüllermeierPublished in: UAI (2023)
Keyphrases
- conditional entropy
- mutual information
- machine learning
- information theoretic measures
- feature selection
- information theoretic
- shannon entropy
- information theory
- similarity measure
- risk measures
- medical image registration
- bayes error rate
- handling uncertainty
- image registration
- probability measures
- information gain
- model selection
- artificial intelligence
- normalized mutual information
- data mining
- multimodal image registration
- knowledge acquisition
- conditional mutual information
- machine learning algorithms
- support vector machine
- text mining
- decision trees
- pattern recognition
- epistemic logic
- active learning
- uncertain data
- knn
- machine learning methods
- text classification
- natural language processing
- graph theoretic
- belief functions
- computer science
- model checking
- learning algorithm
- k nearest neighbor