/ / / Tab 3

Research Article

A Novel Multimean Particle Swarm Optimization Algorithm for Nonlinear Continuous Optimization: Application to Feed-Forward Neural Network Training

Table 3

The results of 5-fold cross validation experiment of the proposed MMPSO and PSO.


Dataset	Algorithm	SSE	Training CA (%)	Testing CA (%)

Lymphography	PSO	23.46	89.32	78.67
Lymphography	MMPSO	13.87	91.49	83.67

Iris	PSO	6.72	91.00	90.67
Iris	MMPSO	1.35	97.33	91.67

Wine	PSO	3.86	92.25	87.22
Wine	MMPSO	0.39	99.58	95.56

Glass	PSO	83.60	66.35	55.84
Glass	MMPSO	62.36	69.21	58.14

Shuttle-landing	PSO	2.07	99.51	94.12
Shuttle-landing	MMPSO	1.79	99.51	96.08

Ionosphere	PSO	24.77	93.07	85.35
Ionosphere	MMPSO	20.16	95.79	88.73

Balance-scale	PSO	58.21	90.20	86.56
Balance-scale	MMPSO	35.85	90.24	89.12

Breast cancer	PSO	73.80	98.38	95.14
Breast cancer	MMPSO	59.43	98.57	96.29

Diabetes	PSO	202.39	76.78	72.08
Diabetes	MMPSO	182.54	77.55	78.05

Thyroid	PSO	528.55	92.95	92.83
Thyroid	MMPSO	373.63	93.66	94.01

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