This paper describes the application of a multiobjective GRASP to rule selection, where previously generated simple rules are combined to give rule sets that minimize complexity and misclassfication cost. As rule selection performance depends heavily on the diversity and quality of the previously generated rules, this paper also investigates a range of multiobjective approaches for creating this initial rule set and the effect on the quality of the resulting classifier.
|Number of pages||8|
|Publication status||Published - 2009|
|Event||Genetic and Evolutionary Computational Conference (Gecco 2009) - |
Duration: 1 Jan 2009 → …
|Conference||Genetic and Evolutionary Computational Conference (Gecco 2009)|
|Period||1/01/09 → …|