Multi-objective local search for mining Pittsburgh classification rules
Résumé
This abstract presents a modeling of the classification rule mining problem as a dominance-based multi-objective local search, with Pittsburgh solution encoding, using accuracy and the number of terms as objectives. This solution is then compared to results from literature of 22 rule mining classification algorithms.
Domaines
Recherche opérationnelle [math.OC]| Origine | Fichiers produits par l'(les) auteur(s) |
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