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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)
Moro, S., Cortez, Paulo & Laureano, Raul M. S. (2013). A data mining approach for bank telemarketing using the rminer package and r tool. Working Paper 13/06. 1-22
Exportar Referência (IEEE)
S. M. Moro et al.,  "A data mining approach for bank telemarketing using the rminer package and r tool", in Working Paper 13/06, Lisboa/Portugal, pp. 1-22, 2013
Exportar BibTeX
@unpublished{moro2013_1711706894711,
	author = "Moro, S. and Cortez, Paulo and Laureano, Raul M. S.",
	title = "A data mining approach for bank telemarketing using the rminer package and r tool",
	year = "2013",
	url = "http://bru-unide.iscte.pt/RePEc/pdfs/13-06.pdf"
}
Exportar RIS
TY  - EJOUR
TI  - A data mining approach for bank telemarketing using the rminer package and r tool
T2  - Working Paper 13/06
AU  - Moro, S.
AU  - Cortez, Paulo
AU  - Laureano, Raul M. S.
PY  - 2013
SP  - 1-22
CY  - Lisboa/Portugal
UR  - http://bru-unide.iscte.pt/RePEc/pdfs/13-06.pdf
AB  - Due to the global financial crisis, credit on international markets became more restricted for 
banks, turning attention to internal clients and their deposits to gather funds. This driver led 
to a demand for knowledge about client’s behavior towards deposits and especially their 
response to telemarketing campaigns. 
This work describes a data mining approach to extract valuable knowledge from recent 
Portuguese bank telemarketing campaign data. Such approach was guided by the CRISP- 
-DM methodology and the data analysis was conducted using the rminer package and R 
tool. Three classification models were tested (i.e., Decision Trees, Naïve Bayes and 
Support Vector Machines) and compared using two relevant criteria: ROC and Lift curve 
analysis. Overall, the Support Vector Machine obtained the best results and a sensitive 
analysis was applied to extract useful knowledge from this model, such as the best months 
for contacts and the influence of the last campaign result and having or not a mortgage 
credit on a successful deposit subscription. 
ER  -