Table 6 Performance of the models—with stacking.

Base learners	Stacking model learner	Class	Count	TP	TN	FN	FP		Precision	Recall	F1
GBT RF DT KNN	GBT	HR	272	246	714	28	26		0.897810219	0.904411765	0.901098901
		LR	406	340	565	43	66		0.88772846	0.837438424	0.861850444
		MR	336	282	603	75	54		0.789915966	0.839285714	0.813852814
		Total	1014	868	1882	146	146	Overall →	0.856015779	0.856015779	0.856015779
								Weighted →	0.858021596	0.85601578	0.856474089
GBT RF DT KNN	RF	HR	272	245	714	28	27		0.897435897	0.900735294	0.899082569
		LR	406	334	522	86	72		0.795238095	0.822660099	0.808716707
		MR	336	244	601	77	92		0.760124611	0.726190476	0.742770167
		Total	1014	823	1837	191	191	Overall →	0.811637081	0.811637081	0.811637081
								Weighted →	0.811016864	0.81163708	0.811104752
GBT RF DT KNN	DT	HR	272	242	701	41	30		0.855123675	0.889705882	0.872072072
		LR	406	323	511	97	83		0.769047619	0.795566502	0.782082324
		MR	336	228	595	83	108		0.733118971	0.678571429	0.704791345
		Total	1014	793	1807	221	221	Overall →	0.782051282	0.782051282	0.782051282
								Weighted →	0.780231703	0.78205128	0.780610374
GBT RF DT KNN	KNN	HR	272	203	703	39	69		0.838842975	0.746323529	0.789883268
		LR	406	295	479	129	111		0.695754717	0.726600985	0.710843373
		MR	336	216	546	132	120		0.620689655	0.642857143	0.631578947
		Total	1014	714	1728	300	300	Overall →	0.704142012	0.704142012	0.704142012
								Weighted →	0.709263736	0.70414201	0.705780261

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