Study on Intelligent Diagnosis of Rotor Fault Causes with the PSO-XGBoost Algorithm

Table 1

Parameters to be optimized.

Parameter	Default value	Range	Explain
Eta	0.3	(0, 1)	Learning rate.
Subsample	1	(0, 1)	Subsample ration of the training instance.
colsample_bytree	1	(0, 1)	Subsample ration of columns when constructing each tree.
colsample_bylevel	1	(0, 1)	Subsample ration of columns for each level.
reg_alpha	0	(0, ∞)	L1 regularization term on weights
reg_lambda	1	(0, ∞)	L2 regularization term on weights.