Representing Classification Problems in Genetic Programming

@inproceedings{Loveard2001RepresentingCP,
  title={Representing Classification Problems in Genetic Programming},
  author={Thomas Loveard and Victor Ciesielski},
  year={2001}
}
In this paper five alternative methods are proposed to perform multi-class classification tasks using genetic programming. These methods are: Binary decomposition, in which the problem is decomposed into a set of binary problems and standard genetic programming methods are applied; Static range selection, where the set of real values returned by a genetic program is divided into class boundaries using arbitrarily chosen division points; Dynamic range selection in which a subset of training… CONTINUE READING
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