Table 2.

Control parameters used for the development and application of soft computing techniques.

	Parameters	Value
GradientBoosting	n-estimators	45
	Max depth	7
	Learning rate	0.10
	Subsample	1
	Alpha	0.90
	Min samples split	2
XGBoost	n-estimators	99
	Max depth	9
	Learning rate	0.07
	Subsample	0.75
	Gamma	0
	Col sample by tree	1
CatBoost	Depth	8
	Learning rate	0.07
	Iterations	700
	Best model min trees	1
	Bootstrap type	MVS
	Leaf estimation method	Newton