Rule induction
From Infogalactic: the planetary knowledge core
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.
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)
Algorithms
Some rule induction algorithms are:
References
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