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Genetic Programming Approach to Benelearn 99: I

Langdon, WB; (1999) Genetic Programming Approach to Benelearn 99: I. In: Putten, PVD and Someren, MV, (eds.) (pp. 3.5-3.5). : Sociaal-Wetenschappelijke Informatica, Universiteit van Amsterdam.

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Abstract

We briefly describe our first genetic programming technique used to automatically evolve profiles of potential insurance customers the task is part of the Benelearn’99 competition. The information about customers consists of 86 variables and includes product usage data and socio-demographic data derived from zip codes. The data was supplied by the Dutch data mining company Sentient Machine Research, and is based on real world business data. Profiles which correctly identified more than 40 percent of customers were automatically evolved using genetic programming.

Type: Proceedings paper
Title: Genetic Programming Approach to Benelearn 99: I
Publisher version: http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers...
Additional information: keywords: genetic algorithms, genetic programming size: 3 pages notes: http://www.swi.psy.uva.nl/benelearn99/comppage.html Note WBL.benelearn2.99.pdf contains version II update (5 pages)
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: http://discovery.ucl.ac.uk/id/eprint/1327842
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