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International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems

IEA/AIE 2005: Innovations in Applied Artificial Intelligence pp 544–546Cite as

Application of a Genetic Algorithm to Nearest Neighbour Classification

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3533))

Abstract

This paper describes the application of a genetic algorithm to nearest-neighbour based imputation of sample data into a census data dataset. The genetic algorithm optimises the selection and weights of variables used for measuring distance. The results show that the measure of fit can be improved by selecting imputation variables using a genetic algorithm. The percentage of variance explained in the goal variables increases compared to a simple selection of imputation variables. This quantitative approach to the selection of imputation variables does not deny the importance of expertise. Human expertise is still essential in defining the optional set of imputation variables.

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References

  1. Vrolijk, H.C.J.: STARS: statistics for regional studies. In: Poppe, K.J. (ed.) Proc. of Pacioli 11 New roads for farm accounting and FADN, LEI, The Hague (2004) ISBN 90-5242-878-6

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  2. Ramos, V., Muge, F.: Less is More: Genetic Optimisation of Nearest Neighbour Classifiers. In: Muge, F., Pinto, C., Piedade, M. (eds.) Proc. of RecPad 1998, Lisbon (1998) ISBN 972-97711-0-3

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  3. Stone, M.: Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society B(36), 111–147 (1974)

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Author information

Authors and Affiliations

  1. Lei Wageningen UR, Burg. Patijnln. 19, den Haag, Netherlands

    Semen Simkin, Tim Verwaart & Hans Vrolijk

Authors
  1. Semen Simkin
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  2. Tim Verwaart
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  3. Hans Vrolijk
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Texas State University-San Marcos, Nueces 247, 601 University Drive, 78666-4616, San Marcos, TX, USA

    Moonis Ali

  2. Dipartimento di Informatica, Università degli Studi di Bari,  

    Floriana Esposito

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© 2005 Springer-Verlag Berlin Heidelberg

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Cite this paper

Simkin, S., Verwaart, T., Vrolijk, H. (2005). Application of a Genetic Algorithm to Nearest Neighbour Classification. In: Ali, M., Esposito, F. (eds) Innovations in Applied Artificial Intelligence. IEA/AIE 2005. Lecture Notes in Computer Science(), vol 3533. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11504894_73

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  • DOI: https://doi.org/10.1007/11504894_73

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26551-1

  • Online ISBN: 978-3-540-31893-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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