Skip to main content

Table 2 The parameter settings for the relevant methods

From: A new fruit fly optimization algorithm enhanced support vector machine for diagnosis of breast cancer based on high-level features

Algorithm Parameter Value
LFOA ax, ay 20,20
bx, by 10,10
FOA ax, ay 20,20
bx, by 10,10
GA crossover 0.4
mutation 0.01
PSO c 1 , c 2 2
w 1
v max 6
MFO a a[−1–2]
b 1
BA (bat algorithm) Q Q[0 2]
A 0.5
r 0.5
DA (dragon fly algorithm) w w[0.9 0.2]
s 0.1
a 0.1
c 0.7
f 1
e 1
FPA (flower pollination algorithm) p 0.8
λ 1.5
SCA (sine cosine algorithm) a 2
RF Number of trees (ntree) 500
Number of variables (mtry) 3
BPNN Number of hidden neurons 8
Type of activation function Sigmoid
Learning algorithm tranlim
ELM Number of hidden neurons 50
Type of activation function Sigmoid