FOLD-R++: A Toolset for Automated Inductive Learning of Default Theories from Mixed Data.
Huaduo WangGopal GuptaPublished in: CoRR (2021)
Keyphrases
- inductive learning
- mixed data
- default theories
- default logic
- knowledge acquisition
- lazy learning
- data sets
- autoepistemic logic
- data compression
- domain theory
- knn
- machine learning
- mixture of gaussian distributions
- answer set programming
- inductive logic programming
- nonmonotonic reasoning
- similarity function
- nonmonotonic logics
- default reasoning
- clustering algorithm
- logic programming
- classical logic
- data model
- decision trees