Artigo em revista científica Q1
Mutual information and sensitivity analysis for feature selection in customer targeting: a comparative study
Néstor Ruben Barraza (Barraza, N.); Sérgio Moro (Moro, S.); Marcelo Ferreyra (Ferreyra, M.); Adolfo de la Peña (de la Peña, A.);
Título Revista
Journal of Information Science
Reino Unido
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(Última verificação: 2019-01-20 14:39)

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N.º de citações: 1

(Última verificação: 2019-01-23 20:59)

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Feature selection is a highly relevant task in any data-driven knowledge discovery project. The present research focuses on analysing the advantages and disadvantages of using mutual information (MI) and data-based sensitivity analysis (DSA) for feature selection in classification problems, by applying both to a bank telemarketing case. A logistic regression model is built on the tuned set of features identified by each of the two techniques as the most influencing set of features on the success of a telemarketing contact, in a total of 13 features for MI and 9 for DSA. The latter performs better for lower values of false positives while the former is slightly better for a higher false-positive ratio. Thus, MI becomes a better choice if the intention is reducing slightly the cost of contacts without risking losing a high number of successes. However, DSA achieved good prediction results with less features.
Customer targeting,Direct marketing,Feature selection,Modelling,Mutual information,Sensitivity analysis
  • Ciências da computação e da informação - Ciências Naturais
  • Ciências da comunicação - Ciências Sociais
Registos de financiamentos
Referência de financiamento Entidade Financiadora
32/15 201 Universidad Nacional de Tres de Febrero
UID/MULTI/0446/2013 Fundação para a Ciência e a Tecnologia