Designing a classifier by a layered multi-population genetic programming approach

  title={Designing a classifier by a layered multi-population genetic programming approach},
  author={Jung-Yi Lin and Hao-Ren Ke and Been-Chian Chien and Wei-Pang Yang},
  journal={Pattern Recognition},
This paper proposes a method called layered genetic programming (LAGEP) to construct a classifier based on multi-population genetic programming (MGP). LAGEP employs layer architecture to arrange multiple populations. A layer is composed of a number of populations. The results of populations are discriminant functions. These functions transform the training set to construct a new training set. The successive layer uses the new training set to obtain better discriminant functions. Moreover… CONTINUE READING
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