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Ass. Lect. Mahmoud Sobhy Ali Hassan :: Publications:

Feature Selection Approach for Chemical Compound Classification based on CSO and PSO
Authors: Mahmoud Sobhy; Ahmed Alsawy; Mahmoud Moussa
Year: 2018
Keywords: molecular classification; Chicken swarm optimization; Particle swarm optimization; feature selection
Journal: Journal of Convergence Information Technology
Volume: Not Available
Issue: Not Available
Pages: Not Available
Publisher: Not Available
Local/International: International
Paper Link: Not Available
Full paper Not Available
Supplementary materials Not Available

with the improvement of profoundly efficient chemoinformatics data collection technology, classification of chemical data emerges as a vital topic in chemoinformatics. Towards building highly accurate predictive models for chemical data, here we introduce two feature selection algorithms. The first algorithm based on Chicken swarm optimization (FS-CSO) and the second algorithm based on Particle swarm optimization (FS-PSO). The proposed algorithms were applied to four datasets and FS-CSO proves advance over FS-PSO. Also, the two algorithms compared against two previous algorithms, BPSO-BP and BPSO-PSO, that used in feature selection for molecular classification and FS-CSO proves advance over them as well

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