Filtrado de SPAM en SMS mediante algoritmos de aprendizaje automático
Keywords:
Machine Learning, SMS, Super Vector Machine, logistic regression, KNN, RandomForest, AdaBoostAbstract
One of the most common forms of communication using mobile phones is through SMS, or short message service. Financial institutions, television companies and the telephone operators are examples of companies that takes advantage of this type of communication; however, this technology is not exempt from unwanted messages or SPAM. This article describes both the application of automatic learning algorithms for SPAM's filter and an experimenting with a data set of 5,574 SMS to evaluate the performance of models using techniques such as Logistic Regression, Super Vector Machine, KNN, Random Forest and AdaBoost to filter and predict unwanted messages.
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