%0 Conference Paper %1 riquelme:2001:IEA %A Riquelme, Jose C. %A Giraldez, Raul %A Aguilar, Jesus S. %A Ruiz, Roberto %B 14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2001) %C Budapest %D 2001 %E Monostori, L. %E Vancza, J. %E Ali, Moonis %I Springer-Verlag %K algorithms, classification, dynamical genetic programming, systems %P 428--433 %T Separation Surfaces Through Genetic Programming %U http://link.springer-ny.com/link/service/series/0558/papers/2070/20700428.pdf %V 2070 %X The aim of this paper is to describe a study for the obtaining, symbolically, of the separation surfaces between clusters of a labelled database. A separation surface is an equation with the form , where is a function of . The calculation of function is begun by the development of the parametric regression by means of the use of the Genetic Programming. The symbolic regression consists in approximating an unknown function's equation, through knowledge of certain points' coordinates and the value that a function reaches with the same ones. This possibility was propose in Koza92a and its advantage in front of the classic statistical regressions is that it is not necessary previously to know the form the function. Once this surface is found, a classifier for the database could be obtained. The technique has been applied to different examples and the results have been very satisfactory.

@inproceedings{riquelme:2001:IEA, abstract = {The aim of this paper is to describe a study for the obtaining, symbolically, of the separation surfaces between clusters of a labelled database. A separation surface is an equation with the form , where is a function of . The calculation of function is begun by the development of the parametric regression by means of the use of the Genetic Programming. The symbolic regression consists in approximating an unknown function's equation, through knowledge of certain points' coordinates and the value that a function reaches with the same ones. This possibility was propose in [Koza92a] and its advantage in front of the classic statistical regressions is that it is not necessary previously to know the form the function. Once this surface is found, a classifier for the database could be obtained. The technique has been applied to different examples and the results have been very satisfactory.}, added-at = {2008-06-19T17:46:40.000+0200}, address = {Budapest}, author = {Riquelme, Jose C. and Giraldez, Raul and Aguilar, Jesus S. and Ruiz, Roberto}, biburl = {https://www.bibsonomy.org/bibtex/2727f7668bf2100fb741eb02978525bb4/brazovayeye}, booktitle = {14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2001)}, editor = {Monostori, L. and Vancza, J. and Ali, Moonis}, interhash = {d3a57711b9d15e94acc2e31892f1c7ba}, intrahash = {727f7668bf2100fb741eb02978525bb4}, keywords = {algorithms, classification, dynamical genetic programming, systems}, month = {4-7 June}, notes = {(Departamento de Lenguajes y Sistemas Informaticos) IEA/AIE-2001 ghostview barfs at ieaqPqaie01_pg.ps but it prints ok on HP printer.}, pages = {428--433}, publisher = {Springer-Verlag}, publisher_address = {Heidelberg}, series = {Lecture Notes in Computer Science}, timestamp = {2008-06-19T17:50:16.000+0200}, title = {Separation Surfaces Through Genetic Programming}, url = {http://link.springer-ny.com/link/service/series/0558/papers/2070/20700428.pdf}, volume = 2070, year = 2001 }