Mining direct marketing data by ensembles of weak learners and rough set methods

Authors:
Jerzy Błaszczyński;Krzysztof Dembczyński;Wojciech Kotłowski;Mariusz Pawłowski
Affiliations:
Institute of Computing Science, Poznań University of Technology, Poznań, Poland;Institute of Computing Science, Poznań University of Technology, Poznań, Poland;Institute of Computing Science, Poznań University of Technology, Poznań, Poland;Acxiom Polska, Warszawa, Poland
Venue:
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
Year:
2006

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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.