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Mining Direct Marketing Data by Ensembles of Weak Learners and Rough Set Methods

  • Jerzy Błaszczyński
  • Krzysztof Dembczyński
  • Wojciech Kotłowski
  • Mariusz Pawłowski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4081)

Abstract

This paper describes problem of prediction that is based on direct marketing data coming from Nationwide Products and Services Questionnaire (NPSQ) prepared by Polish division of Acxiom Corporation. The problem that we analyze is stated as prediction of accessibility to Internet. Unit of the analysis corresponds to a group of individuals in certain age category living in a certain building located in Poland. We used several machine learning methods to build our prediction models. Particularly, we applied ensembles of weak learners and ModLEM algorithm that is based on rough set approach. Comparison of results generated by these methods is included in the paper. We also report some of problems that we encountered during the analysis.

Keywords

Support Vector Machine Weak Learner Rule Induction Decision Class Direct Marketing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jerzy Błaszczyński
    • 1
  • Krzysztof Dembczyński
    • 1
  • Wojciech Kotłowski
    • 1
  • Mariusz Pawłowski
    • 2
  1. 1.Institute of Computing SciencePoznań University of TechnologyPoznańPoland
  2. 2.Acxiom PolskaWarszawaPoland

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