Portal de Periódicos da CAPES

Detección automática de spam utilizando regresión logística bayesiana

2005; Technical University of Valencia; Volume: 35; Issue: 35 Linguagem: Inglês

1135-5948

Antonio Jesús Ortiz Martos, María Teresa Martín Valdivia, Luís Alfonso Ureña López, Miguel Ángel García Cumbreras,

Data Stream Mining Techniques

This paper presents an Spam automatic detection system using Bayesian Logistic Regression (BBR) as machine learning algorithm, over the SPAMBASE collection. We have also used two machine learning algorithms: SVM and PLAUM, in order to compare the results. Our aim is to check the efficiency and effectiveness of the BBR method. The obtained results show good results in terms of precision and recall. We have also noticed that BBR is the faster algorithm