Knowledge discovery in a direct marketing case using least squares support vector machines

DOI10.1002/int.1047zbMath0995.90054OpenAlexW2084347746MaRDI QIDQ4328847

Johan A. K. Suykens, Bart De Moor, Guido Dedene, Bart Baesens, Tony van Gestel, Dirk Van den Poel, Stijn Viaene, Jan Vanthienen

Publication date: 29 April 2002

Published in: International Journal of Intelligent Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/int.1047

zbMATH Keywords

marketingleast squares support vector machine

Mathematics Subject Classification ID

Case-oriented studies in operations research (90B90) Marketing, advertising (90B60)

Related Items (8)

Quantitative models for direct marketing: A review from systems perspective ⋮ Computer assisted customer churn management: state-of-the-art and future trends ⋮ Using support vector machines to learn the efficient set in multiple objective discrete optimization ⋮ Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting ⋮ Support Vector Machine Usingk-Spatial Medians Clustering and Recovery Process ⋮ The impact of preprocessing on data mining: an evaluation of classifier sensitivity in direct marketing ⋮ Bayesian neural network learning for repeat purchase modelling in direct marketing ⋮ Weighted Support Vector Machine Usingk-Means Clustering

Cites Work

• The attrition of volunteers
• Optimal Mailing of Catalogs: A New Methodology Using Estimable Structural Dynamic Programming Models
• Mailing Decisions in the Catalog Sales Industry
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