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Information Theory based Feature Selection for Customer Classi fication
Néstor Ruben Barraza (Néstor Barraza); Sérgio Moro (Moro, S.); Marcelo Ferreyra (Marcelo Ferreyra); Adolfo de la Peña (Adolfo de la Peña);
Event Title
JAIIO-Jornadas Argentinas de Informática
Year (definitive publication)
2016
Language
English
Country
Argentina
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Abstract
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 classifi ed clients.
Acknowledgements
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Keywords
Customer segmentation,feature selection,mutual information