Multi-class pattern classification using single, multi-dimensional feature-space feature extraction evolved by multi-objective genetic programming and its application to network intrusion detection

Abstract

In this paper we investigate using multi-objective genetic programming to evolve a feature extraction stage for multiple-class classifiers. We find mappings which transform the input space into a new, multi-dimensional decision space to increase the discrimination between all classes; the number of dimensions of this decision space is optimized as part of… (More)
DOI: 10.1007/s10710-011-9143-4

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Cite this paper

@article{Badran2011MulticlassPC, title={Multi-class pattern classification using single, multi-dimensional feature-space feature extraction evolved by multi-objective genetic programming and its application to network intrusion detection}, author={Khaled M. S. Badran and Peter Rockett}, journal={Genetic Programming and Evolvable Machines}, year={2011}, volume={13}, pages={33-63} }