ANALYSIS OF MACHINE LEARNING ALGORITHMS USED FOR SHORT MESSAGE SERVICE (SMS) SPAM CLASSIFICATION

SMS, or short message service, is a vital instrument for communication on a global scale. SMS is a marketing tool used by businesses, but regrettably some people exploit it to send spam. Worldwide, these spam and promotional texts are frequently received by smartphone users. The work[1] reviewed here examines a paradigm for categorizing spam, promotional, and ham messages using standard text messages. 4,125 text messages were used to train the model and 1,260 to test it. The classifiers were evaluated using a 10-fold cross validation approach, and the findings indicate that XGBoost, Multinomial Logistic Regression, Support Vector Machine, and Random Forest are some of the top models for a multi - class classification of useful and spam SMS.