Developing Postfix-GP Framework for Symbolic Regression Problems
This is an incremental tool for researchers and practitioners in symbolic regression, offering a user-friendly interface and implementation details.
The paper tackles symbolic regression problems by developing Postfix-GP, a postfix notation-based Genetic Programming framework with a graphical user interface for configuration, visualization, and analysis, and demonstrates it on a benchmark problem.
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.