Representing Classification Problems in Genetic Programming

  title={Representing Classification Problems in Genetic Programming},
  author={Thomas Loveard and Victor Ciesielski},
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
Highly Influential
This paper has highly influenced 20 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 243 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 136 extracted citations

Image descriptor: A genetic programming approach to multiclass texture classification

2015 IEEE Congress on Evolutionary Computation (CEC) • 2015
View 9 Excerpts
Highly Influenced

A scalable genetic programming multi-class ensemble classifier

2009 World Congress on Nature & Biologically Inspired Computing (NaBIC) • 2009
View 4 Excerpts
Highly Influenced

Image Retrieval Using Texture Segmentation by Genetic Programming

View 4 Excerpts
Highly Influenced

244 Citations

Citations per Year
Semantic Scholar estimates that this publication has 244 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 14 references

Genetic Programming for Multiple Class Object Detection

Australian Joint Conference on Artificial Intelligence • 1999
View 1 Excerpt

Pattern classification using a hybrid genetic program decision tree approach

Robert E. Marmelstein, Gary B. Lamont
Genetic Programming • 1998
View 1 Excerpt

Montana . Strongly typed genetic program

John R. Koza, J. David
Evolutionary Computation • 1995

Strongly Typed Genetic Programming

Evolutionary Computation • 1995
View 1 Excerpt

Similar Papers

Loading similar papers…