Enhanced Genetic Algorithm for Optimized Classification

Genetic algorithm (GA) is a well-known adaptive nature inspired technique that utilized in various applications and research domains. This research proposes an Enhanced Genetic Algorithm (EGA) inspired by Genetic Engineering. In EGA, the process of chromosome generation is interfered based on the intercorrelation between genes such that the highly correlated genes are treated. The proposed EGA were employed to optimize the classification results using Support Vector Machine (SVM) on the “Spambase” popular dataset. Experimental results show that classification results were more optimized using EGA as compared to basic GA optimization. The classification results were enhanced using the proposed Enhanced Genetic Algorithm (EGA).