QFC: A Parallel Software Tool for Feature Construction, Based on Grammatical Evolution
Ioannis G. Tsoulos
Abstract
This paper presents and analyzes a programming tool that implements a method for classification and function regression problems. This method builds new features from existing ones with the assistance of a hybrid algorithm that makes use of artificial neural networks and grammatical evolution. The implemented software exploits modern multi-core computing units for faster execution. The method has been applied to a variety of classification and function regression problems, and an extensive comparison with other methods of computational intelligence is made.
Topics & Concepts
Computer scienceGrammatical evolutionFeature (linguistics)SoftwareArtificial intelligenceVariety (cybernetics)ExploitArtificial neural networkSymbolic regressionMachine learningFunction (biology)Genetic programmingTheoretical computer scienceData miningProgramming languageEvolutionary biologyLinguisticsPhilosophyComputer securityBiologyEvolutionary Algorithms and ApplicationsMetaheuristic Optimization Algorithms ResearchNeural Networks and Applications