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Feature Selection approach for Chemical Compound Classification based on CSO and PSO

Journal of Convergence Information Technology (JCIT) • 2018
العودة
معلومات البحث
المؤلفون Ahmed Elsawy1, Mahmoud Mousa2, Mahmoud Sobhy3
الكلمات المفتاحية Molecular Classification; Chicken Swarm Optimization; Particle Swarm Optimization; Feature Selection.
المجلة العلمية Journal of Convergence Information Technology (JCIT)
الناشر Not Available
المجلد 13
العدد Not Available
الصفحات 60-69
publication.type International
رابط البحث Open Link
المواد المرفقة Not Available
الملخص
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 FSCSO
proves advance over FS-PSO. Also, the two algorithms compared against two previous
algorithms, BPSO-BP and BPSO-PSO, that used