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Optimizing classification techniques using genetic programming approach

Saraee, M and Sadjady, R 2008, Optimizing classification techniques using genetic programming approach , in: 12th IEEE International Multitopic Conference, Conquering the Horizons of Future Technology (IEEE INMIC 2008), 23-24 December 2008, Karachi, Pakistan.

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    Abstract

    Genetic Programming (GP) is a branch of Genetic Algorithms (GA) that searches for the best operation or computer program in search space of operations. At the same time classification is a data mining technique used to build model of data classes which can be used to predict future trends. In this paper GP has been employed for the implementation of the classification technique. GP properties can facilitate generating new and optimized classification rules that are not discovered bythe existing traditional classification techniques. In addition we will show that GA approach is superior to traditional methods in regard to performance both on time and space requirements for processing.

    Item Type: Conference or Workshop Item (Paper)
    Themes: Media, Digital Technology and the Creative Economy
    Schools: Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering > Data Mining and Pattern Recognition Research Centre
    Journal or Publication Title: Proceedings of IEEE International Multitopic Conference, 2008. INMIC 2008.
    Publisher: IEEE
    Refereed: Yes
    Related URLs:
    Depositing User: Dr Mo Saraee
    Date Deposited: 27 Oct 2011 10:35
    Last Modified: 20 Aug 2013 18:16
    URI: http://usir.salford.ac.uk/id/eprint/18702

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