Developing Postfix-GP Framework for Symbolic Regression Problems
Neural and Evolutionary Computing
2015-07-08 v1
Abstract
This paper describes Postfix-GP system, postfix notation based Genetic Programming (GP), for solving symbolic regression problems. It presents an object-oriented architecture of Postfix-GP framework. It assists the user in understanding of the implementation details of various components of Postfix-GP. Postfix-GP provides graphical user interface which allows user to configure the experiment, to visualize evolved solutions, to analyze GP run, and to perform out-of-sample predictions. The use of Postfix-GP is demonstrated by solving the benchmark symbolic regression problem. Finally, features of Postfix-GP framework are compared with that of other GP systems.
Keywords
Cite
@article{arxiv.1507.01687,
title = {Developing Postfix-GP Framework for Symbolic Regression Problems},
author = {Vipul K. Dabhi and Sanjay Chaudhary},
journal= {arXiv preprint arXiv:1507.01687},
year = {2015}
}
Comments
8 pages, 6 figures