Name
Abstract | ||
|---|---|---|
This paper introduces a new algorithm called SIAO1 for learning first order logic rules with genetic algo- rithms. SIAO1 uses the covering principle developed in AQ where seed examples are generalized into rules using however a genetic search, as initially introduced in the SIA algorithm for attribute-based representa- tion. The genetic algorithm uses a high level rep- resentation for learning rules in first order logic and may deal with numerical data as well as background knowledge such as hierarchies over the predicates or tree structured values. The genetic operators may for instance change a predicate into a more general one according to background knowledge, or change a con- stant into a variable. The evaluation function may take into account user preference biases. |
Year | Venue | Keywords |
|---|---|---|
1995 | KDD | first order logic,genetic operator,genetics,tree structure,genetic algorithm,evaluation function |
Field | DocType | Citations |
Data mining,Genetic operator,Computer science,Evaluation function,First-order logic,Operator (computer programming),Genetic representation,Artificial intelligence,Cultural algorithm,Population-based incremental learning,Genetic algorithm,Machine learning | Conference | 32 |
PageRank | References | Authors |
5.86 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sébastien Augier | 1 | 32 | 5.86 |
| Gilles Venturini | 2 | 660 | 82.45 |
| Yves Kodratoff | 3 | 581 | 172.25 |