This chapter describes the application of evolutionary algorithms to induce predictive models of customer behavior in a business environment. Predictive models are expressed as fuzzy rule bases, which have the interesting property of being easy to interpret for a human expert, while providing satisfactory accuracy. The details of an island-based distributed evolutionary algorithm for fuzzy model induction are presented and a case study is used to illustrate the effectiveness of the approach.
Fuzzy-evolutionary modeling of customer behavior for business intelligence / C.C. Pereira, A.G.B. Tettamanzi (STUDIES IN FUZZINESS AND SOFT COMPUTING). - In: Marketing intelligent systems using soft computing : managerial and research applications / [a cura di] J. Casillas, F.J. Martínez-López. - Berlin : Springer, 2010. - ISBN 9783642156052. - pp. 207-225 [10.1007/978-3-642-15606-9_15]
Fuzzy-evolutionary modeling of customer behavior for business intelligence
C.C. PereiraPrimo
;A.G.B. TettamanziUltimo
2010
Abstract
This chapter describes the application of evolutionary algorithms to induce predictive models of customer behavior in a business environment. Predictive models are expressed as fuzzy rule bases, which have the interesting property of being easy to interpret for a human expert, while providing satisfactory accuracy. The details of an island-based distributed evolutionary algorithm for fuzzy model induction are presented and a case study is used to illustrate the effectiveness of the approach.
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