Exportar Publicação

A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Barraza, N. R., Moro, S., Ferreyra, M. & de la Peña, A. (2016). Information theory based feature selection for customer classification. In 45th JAIIO. Proceedings of ASAI 2016. Simposio Argentino de Inteligencia Artificial. (pp. 1-8). Buenos Aires: SADIO Sociedad Argentina de Informática.
Exportar Referência (IEEE) 
N. R. Barraza et al.,  "Information theory based feature selection for customer classification", in 45th JAIIO. Proc. of ASAI 2016. Simposio Argentino de Inteligencia Artificial, Buenos Aires, SADIO Sociedad Argentina de Informática, 2016, pp. 1-8
Exportar BibTeX 
@inproceedings{barraza2016_1728929750391,
	author = "Barraza, N. R. and Moro, S. and Ferreyra, M. and de la Peña, A.",
	title = "Information theory based feature selection for customer classification",
	booktitle = "45th JAIIO. Proceedings of ASAI 2016. Simposio Argentino de Inteligencia Artificial",
	year = "2016",
	editor = "",
	volume = "",
	number = "",
	series = "",
	pages = "1-8",
	publisher = "SADIO Sociedad Argentina de Informática",
	address = "Buenos Aires",
	organization = "Universidad Nacional de Tres de Febrero (UNTREF)",
	url = "https://45jaiio.sadio.org.ar/node/81"
}
Exportar RIS 
TY  - CPAPER
TI  - Information theory based feature selection for customer classification
T2  - 45th JAIIO. Proceedings of ASAI 2016. Simposio Argentino de Inteligencia Artificial
AU  - Barraza, N. R.
AU  - Moro, S.
AU  - Ferreyra, M.
AU  - de la Peña, A.
PY  - 2016
SP  - 1-8
CY  - Buenos Aires
UR  - https://45jaiio.sadio.org.ar/node/81
AB  - The application of Information Theory techniques in customer feature selection is analyzed. This method, usually called information gain has been demonstrated to be simple and fast for feature selection. The important concept of mutual information, originally introduced to analyze and model a noisy channel is used in order to measure relations between characteristics of given customers. An application to a bank customers data set of telemarketing calls for selling bank long-term deposits is shown. We show that with our method, 80% of the subscribers can be reached by contacting just the better half of the classified clients.
ER  -