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A data mining approach for bank telemarketing using the rminer package and r tool
Título Documento
Working Paper 13/06
Ano (publicação definitiva)
2013
Língua
Inglês
País
Portugal
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Abstract/Resumo
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.
Agradecimentos/Acknowledgements
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