FOLD-R++: A Scalable Toolset for Automated Inductive Learning of Default Theories from Mixed Data.
Huaduo WangGopal GuptaPublished in: FLOPS (2022)
Keyphrases
- inductive learning
- mixed data
- default theories
- default logic
- knowledge acquisition
- machine learning
- data sets
- knn
- data compression
- lazy learning
- mixture of gaussian distributions
- nonmonotonic reasoning
- autoepistemic logic
- answer set programming
- similarity function
- clustering algorithm
- domain theory
- default reasoning
- inductive logic programming
- neural network
- nonmonotonic logics
- ripple down rules