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The upsurge in the volume of unwanted emails called spam has created an intense need for the development of more dependable and robust antispam filters. Machine learning methods of recent are being used to successfully detect and filter spam emails. We present a systematic review of some of the popular machine learning based email spam filtering approaches. Our review covers survey of the important concepts, attempts, efficiency, and the research trend in spam filtering. The preliminarydoi:10.1016/j.heliyon.2019.e01802 pmid:31211254 pmcid:PMC6562150 fatcat:n7qiq4tgnzh7xi6j5c2ah335hy