Multistrategy Self-Organizing Map Learning for Classification Problems

Table 5

Summarisation of SOMPSO and ESOMPSO results.

		SOMPSO			ESOMPSO
		EUC	MAN	CHEBY	EUC	MAN	CHEBY
Iris	Epoch	1000	1000	1000	1000	1000	1000
	Quantisation error	4.0799	4.0979	4.0875	1.8884	2.0125	2.0565
	Convergence error	0.0318	0.0358	0.0322	0.0243	0.0587	0.0347
	Convergence time	22 sec	22 sec	22 sec	240 sec	240 sec	240 sec
	Classification (%)	92.00	89.24	90.45	92.72	90.11	90.75
XOR	Epoch	1000	1000	1000	1000	1000	1000
	Quantisation error	0.5011	0.6455	0.5866	0.0048	0.0250	0.0145
	Convergence error	0.2500	0.3204	0.3050	0.1916	0.2591	0.2641
	Convergence time	10 sec	10 sec	10 sec	17 sec	17 sec	17 sec
	Classification (%)	94.11	85.25	88.47	95.22	86.14	90.24
Cancer	Epoch	1000	1000	1000	1000	1000	1000
	Quantisation error	0.0094	0.0145	0.0102	0.0050	0.0125	0.0078
	Convergence error	0.5951	0.6523	0.6424	0.4422	0.5371	0.4823
	Convergence time	80 sec	80 sec	80 sec	110 sec	110 sec	110 sec
	Classification (%)	90.69	75.23	78.89	91.77	77.35	82.05
Glass	Epoch	1000	1000	1000	1000	1000	1000
	Quantisation error	0.0046	0.0087	0.0052	0.0038	0.0060	0.0048
	Convergence error	0.0435	0.0541	0.1242	0.0157	0.0324	0.0224
	Convergence time	40 sec	40 sec	40 sec	60 sec	60 sec	60 sec
	Classification (%)	87.88	80.98	84.66	89.45	82.45	84.87
Pendigits	Epoch	1000	1000	1000	1000	1000	1000
	Quantization error	0.0458	0.4752	0.4777	0.0587	0.5143	0.4221
	Convergence error	0.2060	0.2365	0.2241	0.1405	0.1569	0.1478
	Convergence time	110 sec	110 sec	110 sec	205 sec	205 sec	205 sec
	Classification (%)	75.44	70.25	72.48	85.62	70.85	72.89

EUC: Euclidean distance, MAN: Manhattan distance, CHEBY: Chebyshev distance.