Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning: Are Conditional Entropy and Mutual Information Appropriate Measures?
Eyke HüllermeierPublished in: CoRR (2022)
Keyphrases
- conditional entropy
- mutual information
- machine learning
- information theoretic measures
- feature selection
- information theoretic
- shannon entropy
- information theory
- image registration
- probability measures
- similarity measure
- risk measures
- bayes error rate
- conditional mutual information
- handling uncertainty
- information gain
- machine learning methods
- information extraction
- multimodal image registration
- computer science
- machine learning algorithms
- supervised learning
- medical image registration
- knowledge acquisition
- text classification
- computer vision
- learning algorithm
- text mining
- data mining
- model selection
- statistical methods
- support vector machine
- uncertain data
- possibility theory
- knowledge representation
- multiresolution
- image analysis
- graphical models
- image segmentation