Table 4 Comparison of the gene selection algorithms using particular datasets with fivefold validation.

		IBPSO	IG_GA	EPSO	mABC	BPSO-GCS-ELM	SIW-APSO-ELM
Leukemia	Accuracy-Avg	98.34 ± 0.02	97.56 ± 0.32	95.11 ± 0.12	99.3 ± 0.01	100 ± 0.00	100 ± 0.00
Brain Cancer	Accuracy-Avg	77.34 ± 0.35	77.23 ± 0.45	74.65 ± 0.32	79.34 ± 0.03	88.3 ± 0.02	90.21 ± 0.04
Colon	Accuracy-Avg	93.45 ± 0.02	94.31 ±	93.23 ± 0.06	97.34 ± 0.09	97.38 ± 0.01	98.45 ± 0.01
SRBCT	Accuracy-Avg	100 ± 0.00	100 ± 0.00	100 ± 0.00	100 ± 0.00	100 ± 0.00	100 ± 0.00
Lung	Accuracy-Avg	95.86 ± 0.89	95.57 ± 0.23	95.67 ± 0.96	96.65 ± 0.56	94.78 ± 0.02	97.62 ± 0.01
Lymphoma	Accuracy-Avg	100 ± 0.00	100 ± 0.00	100 ± 0.00	100 ± 0.00	100 ± 0.00	100 ± 0.00
11_Tumors	Accuracy-Avg	95.06 ± 0.04	92.53 ± 0.07	95.92 ± 0.54	97.78 ± 0.23	97.88 ± 0.02	99.87 ± 0.10
DLBCL	Accuracy-Avg	100 ± 0.00	100 ± 0.00	100 ± 0.00	100 ± 0.00	100 ± 0.00	100 ± 0.00

Bold values in Table 4 indicate the best results. (IBPSO = Improved Binary Particle Swarm Optimization, IG-GA = Information Gain Genetic Algorithm, EPSO = Enhance Binary Particle Swarm. Optimization, mABC = Artificial Bee Colony Algorithm, BPSO-GCS-ELM = Binary Particle Swarm Optimization-Gene to Class Sensitivity-Extreme Learning Machine, SIW-APSO-ELM = Self Inertia Weight Adaptive Particle Swarm Optimization-Extreme Learning Machine).

Quick links

Search