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Multi-objective local search for mining Pittsburgh classification rules

Abstract

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.
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Dates and versions

hal-00749712 , version 1 (08-11-2012)

Identifiers

  • HAL Id : hal-00749712 , version 1

Cite

Julie Jacques, Julien Taillard, David Delerue, Laetitia Jourdan, Clarisse Dhaenens. Multi-objective local search for mining Pittsburgh classification rules. International Conference on Metaheuristics and Nature Inspired Computing, Oct 2012, Port El-Kantaoui, Tunisia. ⟨hal-00749712⟩
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