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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
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
@unpublished{moro2013_1711706894711, author = "Moro, S. and Cortez, Paulo and Laureano, Raul M. S.", title = "A data mining approach for bank telemarketing using the rminer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" }
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 -