Mining the most interesting rules
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Multiobjective Metaheuristics for the Bus Driver Scheduling Problem
Transportation Science
A GRASP Algorithm for the Multi-Objective Knapsack Problem
QEST '04 Proceedings of the The Quantitative Evaluation of Systems, First International Conference
A multi-objective GRASP for partial classification
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Evolutionary and Metaheuristics based Data Mining (EMBDM); Guest Editors: José A. Gámez, María J. del Jesús, José M. Puerta
Rule induction for classification using multi-objective genetic programming
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Evolutionary multi objective optimization for rule mining: a review
Artificial Intelligence Review
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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.