A Gwhsc - A Genetic Algorithm Based Weighted Hybrid Classifier For Sms Spam

Abstract

The proliferation in the volume of unwanted SMS called spam has paved strong need for the development of more reliable and robust anti-spam detectors. In recent years, machine learning algorithms are being successfully used for classifying the datasets which are successfully adopted in many applications. Machine learning methods are also can be applied to detect the SMS spams. Feature selection in Machine Learning process plays a vital role in improving the accuracy and other performance aspects. In this work, a novel GWHSC approach for detecting SMS spam is proposed that utilizes evolutionary method for feature selection which is realized to be the efficient method for spam filtering. Experimental result show that proposed work outperforms well when compared to the existing approaches.