New Dandelion Algorithm Optimizes Extreme Learning Machine for Biomedical Classification Problems

Table 3

Mean value and standard deviation achieved by DA, BA, EFWA, and PSO (accurate to 10⁻⁶).

Function	BA; mean (Std)	EFWA; mean (Std)	PSO; mean (Std)	DA; mean (Std)
Sphere	0.001277; (0.000144)	0.079038; (0.010276)	0.09323; (0.053308)	0.000000; (0.000000)
Schwefel	0.00417; (0.000856)	0.310208; (0.082243)	0.551331; (0.382977)	0.000000; (0.000000)
Rosenbrock	26.94766; (1.396553)	97.43135; (86.30464)	117.0419; (100.6725)	15.88892; (0.262501)
Ackley	2.175684; (0.386022)	11.67335; (9.79794)	6.062462; (1.350912)	0.000000; (0.000000)
Griewank	0.000069; (0.000009)	0.139219; (0.027736)	0.020483; (0.019879)	0.000000; (0.000000)
Rastrigin	29.47549; (7.795089)	130.8502; (22.96112)	63.04136; (15.74571)	0.000000; (0.000000)
Penalized	0.673172; (0.804593)	0.002687; (0.001646)	17.48197; (11.78603)	0.001939; (0.00423)
Six-Hump Camel-Back	−1.03163; (0.000000)	−1.03163; (0.000000)	−1.03163; (0.000000)	−1.03163; (0.000000)
Goldstein-Price	13.05883; (18.67556)	3.000000; (0.000000)	6.176471; (15.87918)	3.000000; (0.000000)
Schaffer	0.004731; (0.006673)	0.000000; (0.000000)	0.005302; (0.00666)	0.000000; (0.000000)
Axis Parallel Hyper Ellipsoid	0.023513; (0.004702)	0.00306; (0.000568)	1.743886; (1.521884)	0.000000; (0.000000)
Rotated Hyper Ellipsoid	0.024743; (0.005611)	0.490085; (0.073349)	1.30426; (2.23374)	0.000000; (0.000000)