GFLIB: an Open Source Library for Genetic Folding Solving Optimization Problems

Authors

  • Mohammad A. Mezher Fahd Bin Sultan University

DOI:

https://doi.org/10.30564/aia.v1i1.608

Abstract

This paper aims at presenting GFLIB, a Genetic Folding MATLAB toolbox for supervised learning problems. In essence, the goal of GFLIB is to build a concise model of supervised learning, and a free open source MATLAB toolbox for performing classification and regression. The GFLIB is specifically designed for most of the traditionally used features, to evolve in applications of mathematical models. The toolbox suits all kinds of users; from the users who implemented GFLIB as “black box”, to advanced researchers who want to generate and test new functionalities and parameters of GF algorithm. The toolbox and its documentation are freely available for download at: https://github.com/mohabedalgani/gflib.git 

Keywords:

GF toolbox; GF Algorithm; Evolutionary algorithms; Classification; Regression; Optimization; LIBSVM

References

[1] Seyedali Mirjalili. Evolutionary Algorithms and Neural Networks Theory and Applications. Springer international Publishing; June 2018.

[2] Sara Silva and Jonas Almeida, “Gplab-a genetic programming toolbox for matlab,” In Proc. of the Nordic MATLAB Conference, pp. 273--278, 2005.

[3] A.J. Chipperfield and P.J. Fleming, “The MATLAB genetic algorithm toolbox”, IEE Colloquium on Applied Control Techniques Using MATLAB, UK, 1995

[4] Mezher, Mohammad and Abbod, Maysam. (2010). Genetic Folding: A New Class of Evolutionary Algorithms. 279-284.

[5] Mohd Mezher, Maysam Abbod. Genetic Folding: An Algorithm for Solving Multiclass SVM Problems. Applied Soft Computing, Elsiver Journal. 41(2):464-472. 2014.

[6] C L Blake, C J Merz. UCI repository of machine learning databases University of California, Irvine, Department of Information and Computer Sciences. 1998.

[7] Chang, Chih-Chung and Lin, Chih-Jen. LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology. 2(3): 1-27. 20011.

[8] Mohd Mezher, Maysam Abbod. Genetic Folding: A New Class of Evolutionary Algorithms. October 2010.

[9] Mohd Mezher, Maysam Abbod. A New Genetic Folding Algorithm for Regression Problems. Proceedings - 2012 14th International Conference on Modelling and Simulation, UKSim. 46-51. 2012.

[10] R. A. Fisher (1936). "The use of multiple measurements in taxonomic problems". Annals of Eugenics. 7 (2): 179–188.

[11] Statistics and Machine Learning Toolbox Users guide. 2018b,the MathWorks, Inc., Natick, Massachusetts, United States.

Downloads

How to Cite

Mezher, M. A. (2019). GFLIB: an Open Source Library for Genetic Folding Solving Optimization Problems. Artificial Intelligence Advances, 1(1), 11–17. https://doi.org/10.30564/aia.v1i1.608

Issue

Article Type

Article