Construção de Conjunto de Classificadores Baseado na Diversidade do Espaço de Características e Algoritmos de Aprendizagem para Detecção de Spam
Abstract
Research in the class machines area focus their efforts on diversity for the construction ensemble classifiers. The concept of diversity is related to the resources used to develop ensemble classifiers. It is demonstrated that diversity over learning algorithms performs better than feature manipulation capabilities. Showing considerable reduction of false positives in problem spam classification, in addition to the other metrics addressed as precision, accuracy, measure-f1 and recall.
References
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Díez-Pastor, J. F., Rodríguez, J. J., García-Osorio, C. I., and Kuncheva, L. I. (2015). Diversity techniques improve the performance of the best imbalance learning ensembles. volume 325, pages 98–117. Elsevier.
Easwaramoorthy, S., Thamburasa, S., Aravind, K., Bhushan, S. B., and Rajadurai, H. (2016). Heterogeneous classifier model for e-mail spam classification using fso feature selection method. In Inventive Computation Technologies (ICICT), International Conference on, volume 1, pages 1–6. IEEE.
Ibrahim, A. J., Siraj, M. M., and Din, M. M. (2017). Ensemble classifiers for spam review detection. In Application, Information and Network Security (AINS), 2017 IEEE Conference on, pages 130–134. IEEE.
Symantec (2018). Monthly threat report, Acessado em 20 de Junho de 2018. [link].
Yin, X.-C., Huang, K., Hao, H.-W., Iqbal, K., and Wang, Z.-B. (2014). A novel classifier ensemble method with sparsity and diversity. In Neurocomputing, volume 134, pages 214–221. Elsevier.
Published
2018-10-25
How to Cite
LUTZ, Gabriel P.; OST, Lucas; HENKE, Márcia.
Construção de Conjunto de Classificadores Baseado na Diversidade do Espaço de Características e Algoritmos de Aprendizagem para Detecção de Spam. In: WORKSHOP ON SCIENTIFIC INITIATION AND UNDERGRADUATE WORKS - BRAZILIAN SYMPOSIUM ON CYBERSECURITY (SBSEG), 18. , 2018, Natal.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
p. 185-188.
DOI: https://doi.org/10.5753/sbseg_estendido.2018.4156.
