AutoScore-Ordinal: An Interpretable Machine Learning Framework for Generating Scoring Models for Ordinal Outcomes.
Seyed Ehsan SaffariYilin NingFeng XieBibhas ChakrabortyVictor VoloviciRoger VaughanMarcus Eng Hock OngNan LiuPublished in: AMIA (2022)
Keyphrases
- machine learning
- probabilistic model
- machine learning methods
- data driven approaches
- machine learning algorithms
- modeling framework
- mathematical framework
- pattern recognition
- knowledge discovery
- text mining
- main contribution
- machine learning approaches
- statistical models
- neural network
- active learning
- statistical inference
- bayesian framework
- learning algorithm
- complex systems
- theoretical framework
- decision trees
- knowledge acquisition
- computational intelligence
- supervised learning
- information extraction