A Novel Genetic Programming Based Approach for Classification Problems

A new genetic programming based approach to classification problems is proposed. Differently from other approaches, the number of prototypes in the classifier is not a priori fixed, but automatically found by the system. In fact, in many problems a single class may contain a variable number of subclasses. Hence, a single prototype, may be inadequate to represent all the members of the class. The devised approach has been tested on several problems and the results compared with those obtained by a different genetic programming based approach recently proposed in the literature.

[1]  Nikhil R. Pal.  Pattern Recognition in Soft Computing Paradigm , 2001 .

[2]  Shigeo Abe DrEng.  Pattern Classification , 2001, Springer London.

[3]  Nikhil R. Pal,et al.  A novel approach to design classifiers using genetic programming , 2004, IEEE Transactions on Evolutionary Computation.

[4]  Lothar Thiele,et al.  A Comparison of Selection Schemes used in Genetic Algorithms , 1995 .

[5]  Lalit M. Patnaik,et al.  Application of genetic programming for multicategory pattern classification , 2000, IEEE Trans. Evol. Comput..

[6]  Jason M. Daida,et al.  Classification of Spectral Image Using Genetic Programming , 2000, GECCO.

[7]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[8]  Luca Lombardi,et al.  Image classification: an evolutionary approach , 2002, Pattern Recognit. Lett..

[9]  David G. Stork,et al.  Pattern Classification , 1973 .

[10]  John R. Koza,et al.  Genetic programming as a means for programming computers by natural selection , 1994 .

[11]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[12]  Jason M. Daida,et al.  Classification of spectral imagery using genetic programming , 2000 .

[13]  Mario Köppen,et al.  Genetic programming based texture filtering framework , 2000 .

[14]  Catherine Blake,et al.  UCI Repository of machine learning databases , 1998 .

[15]  Andreas Bastian.  Identifying fuzzy models utilizing genetic programming , 2000, Fuzzy Sets Syst..