Enhanced genetic algorithm for spam detection in email

Spam detection is one of the major problem, for which an enhanced genetic algorithm (EGA) was proposed in this paper. Proposed EGA was to achieve the best chromosomes which were grouped by the keywords. Then, the best chromosome with highest fitness value was selected as classifier. Metropolis sample process of simulated annealing (SA) was used with classical mutation and crossover to reinforce the efficiency of genetic searches and provide mature convergence. Achieved results represent the enhanced GA was markedly superior to that of a classical GA.