Ciência-IUL
Publicações
Descrição Detalhada da Publicação
Mutual information and sensitivity analysis for feature selection in customer targeting: a comparative study
Título Revista
Journal of Information Science
Ano (publicação definitiva)
2019
Língua
Inglês
País
Reino Unido
Mais Informação
Web of Science®
Scopus
Google Scholar
Abstract/Resumo
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.
Agradecimentos/Acknowledgements
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Palavras-chave
Customer targeting,Direct marketing,Feature selection,Modelling,Mutual information,Sensitivity analysis
Classificação Fields of Science and Technology
- 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 |