Rule induction
From Wikipedia, the free encyclopedia
Rule induction is an area of machine learning in which formal rules are extracted from a set of observations. The rules extracted may represent a full scientific model of the data, or merely represent local patterns in the data.
[edit] Paradigms
Some major rule induction paradigms are:
- Association rule algorithms (e.g., Aggrawal)
- Decision rule algorithms (e.g., Quinlan 1987)
- Hypothesis testing algorithms (e.g., RULEX)
- Horn clause induction
- Version spaces
- Rough set rules
- Inductive Logic Programming
- Boolean decomposition (Feldman)
[edit] Algorithms
Some rule induction algorithms are:
- Charade
- Rulex
- Progol
- CN2
[edit] References
- Quinlan, J. R. (1987). "Generating production rules from decision trees". McDermott, John Proceedings of the Tenth International Joint Conference on Artificial Intelligence (IJCAI-87): 304–307.