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

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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

Vol. 1 , Iss. 1 (April 2019)

Article Type

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