Solving Feature Subset Selection Problem by a Hybrid Metaheuristic
نویسندگان
چکیده
The aim of this paper is to develop a hybrid metaheuristic based on Variable Neighbourhood Search and Tabu Search for solving the Feature Subset Selection Problem in classification. Given a set of instances characterized by several features, the classification problem consists of assigning a class to each instance. Feature Subset Selection Problem selects a relevant subset of features from the initial set in order to classify future instances. The proposed hybrid metaheuristic is compared with a Genetic Algorithm proposed in the literature. Although he hybrid metaheuristic and the genetic algorithm had a similar performance according to the accuracy percentages, the hybrid metaheuristic provided a higher reduction in the set of features.
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