Challenges in Individual Representation of GP Classification

Autores

  • Venkatadri M. University of Petroleum and Energy Studies, Dehradun.
  • Hanumat Sastry G University of Petroleum and Energy Studies, Dehradun.
  • Dr. Lokanatha C. Reddy Dravidian University, Kuppam,

Palavras-chave:

genetic programming, data mining, classification, classification issues

Resumo

Genetic Programming (GP) is an evolutionary programming strategy that automatically solves complex problems through computer programs. The field of Data Mining has got engrossed towards GP, due to its advantages in automatic evolution of programs with optimized solutions without prior knowledge on data. The classification technique is among the most studied Data Mining task through GP. GP, despite being used for classification for long time due to its numerous outstanding abilities, still suffers from certain limitations. Hence, this paper focuses on various Individual Representation challenges of GP Classification. 

Biografias do Autor

  • Venkatadri M., University of Petroleum and Energy Studies, Dehradun.
    Centre for Information Technology,Assistant Professor
  • Hanumat Sastry G, University of Petroleum and Energy Studies, Dehradun.
     Centre for Information Technology,Assistant Professor
  • Dr. Lokanatha C. Reddy, Dravidian University, Kuppam,
    Department of Computer Science, Professor

Downloads

Publicado

2013-05-02

Edição

Vol. 4 N.º 1 (2013)

Secção

Research Articles

Licença

Declaration and Copyright Transfer Form

(to be completed by authors)

 

I/ We, the undersigned author(s) of the submitted manuscript, hereby declare, that the above manuscript which is submitted for publication in the STM Journals(s), is not published already in part or whole (except in the form of abstract) in any journal or magazine for private or public circulation, and, is not under consideration of publication elsewhere.

·         I/We will not withdraw the manuscript after 1 week of submission as I have read the Author Guidelines and will adhere to the guidelines.

·         I/We Author(s ) have niether given nor will give this manuscript elsewhere for publishing after submitting in STM Journal(s).

·         I/ We have read the original version of the manuscript and am/ are responsible for the thought contents embodied in it. The work dealt in the manuscript is my/ our own, and my/ our individual contribution to this work is significant enough to qualify for authorship.

·          I/We also agree to the authorship of the article in the following order:

Author’s name                                    

 

1. ________________

2. ________________

3. ________________

4. _______________

 

We  Author(s) tick this box and would request you to consider it as our signature as we agree to the terms of this Copyright Notice, which will apply to this submission if and when it is published by this journal.