Differential diagnosis of Crohn’s disease and intestinal tuberculosis based on ATR-FTIR spectroscopy combined with machine learning

Table 4 Optimal parameters of the XGBoost model based on first-derivative spectral data

Parameters	Step length	Optimal range	AUC (%)		Accuracy (%)
			Optimal value	Test	Optimal value	Test
Max_depth	1.00	(1, 50.0)	3.0	79.9	4.0.	74.5
N_estimators	10.00	-1500	71.0	80.3	81.0	74.4
Min_child_weight	1.00	(1, 30.0)	4.0	82.1	4.0	76.0
Gamma	1.00	(0, 15.0)	0	82.1	0	76.0
Subsample	0.10	(0, 1.1)	1.0.	82.1	1.0.	76.0
Alpha	0.10	(0, 10.0)	0.3	82.0	2.8	75.9
Learning_rate	0.01	(0, 0.2)	0.1	82.0	0.1	75.2

AUC: Area under the curve.