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Classification and Target Group Selection Based Upon Frequent Patterns

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Author Info
Pijls, W.H.L.M.
Potharst, R. (Erasmus Research Institute of Management (ERIM), RSM Erasmus University)
Abstract

In this technical report , two new algorithms based upon frequent patterns are proposed. One algorithm is a classification method. The other one is an algorithm for target group selection. In both algorithms, first of all, the collection of frequent patterns in the training set is constructed. Choosing an appropriate data structure allows us to keep the full collection of frequent patterns in memory. The classification method utilizes directly this collection. Target group selection is a known problem in direct marketing. Our selection algorithm is based upon the collection of frequent patterns.

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File URL: http://hdl.handle.net/1765/50
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Publisher Info
Paper provided by Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam. in its series Research Paper with number ERS-2000-40-LIS Revision_Date: 2009-12-18.

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Date of creation: 20 Oct 2000
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Handle: RePEc:dgr:eureri:200043

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Related research
Keywords: classification; target group selection; association rules; frequent item sets;

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This page was last updated on 2009-12-23.


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