SMS spam detection and comparison of various machine learning algorithms
Paras Sethi, Vaibhav Bhandari, Bhavna Kohli · 2017
Past few years have seen increase in the number of spam emails and messages. Legal, economic and technical measures can be used to tackle spam sms's nowadays. A key role is being played by Bayesian filters in stopping this problem. In this paper, we analyzed and studied the relative strengths of various machine learning algorithms in order to detect spam messages which are sent on mobile devices. We have acquired the data from on open public dataset and prepared two datasets for our testing and validation purposes. Accuracy in detecting spam messages was the first priority in ranking these algorithms. Our results clearly demonstrate that different machine learning algorithms under different features tend to perform differently in classifying spam messages.