Adaptive Particle Swarm Optimization Algorithm Ensemble Model Applied to Classification of Unbalanced Data

Table 4

Parameters of all algorithms in the experiments.

Algorithm	Parameters
DT	Min_samples_leaf = 6
	Max_depth = 8
	Min_samples_split = 2
	Gamma = 0.0
	Max_leaf_nodes = 4
LR	No parameters specified
MLP	Epoch = 1000
	Learning_rate = 0.01
	Hidden_units = 5
SVM	Kernel: RBF
	C = 32
	Gamma = 0.1
RF	N_estimators = 100
	Max_features = 12
	Max_depth = 400
	Min_samples_split = 2
	Min_samples_leaf = 1