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Chapter

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Title

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

Authors

[ 1 ] Instytut Informatyki, Wydział Informatyki, Politechnika Poznańska | [ 2 ] Instytut Informatyki (II), Wydział Informatyki i Zarządzania, Politechnika Poznańska | [ P ] employee

Year of publication

2006

Chapter type

paper

Publication language

english

Abstract

EN 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.

Pages (from - to)

218 - 227

DOI

10.1007/11823728_21

URL

https://link.springer.com/chapter/10.1007/11823728_21

Book

Data Warehousing and Knowledge Discovery : 8th International Conference, DaWaK 2006, Krakow, Poland, September 4-8, 2006 : Proceedings

Presented on

8th International Conference on Data Warehousing and Knowledge Discovery DaWaK 2006, 4-8.09.2006, Kraków, Polska

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