Table 3 Performance of the models—without ensemble.

Classifier	Class	Count	TP	TN	FN	FP		Precision	Recall	F1
DT	HR	272	232	704	38	40		0.859259259	0.852941176	0.856088561
	LR	406	319	499	109	87		0.745327	0.785714286	0.76498801
	MR	336	214	576	102	122		0.677215	0.636904762	0.656441718
	Total	1014	765	1779	249	249	Overall →	0.754438	0.754438	0.754438
							Weighted →	0.753319158	0.75443787	0.753457236
RF	HR	272	243	714	28	29		0.896678967	0.893382353	0.895027624
	LR	406	342	519	89	64		0.79350348	0.842364532	0.817204301
	MR	336	236	602	76	100		0.756410256	0.702380952	0.728395062
	Total	1014	821	1835	193	193	Overall →	0.809664694	0.809664694	0.809664694
							Weighted →	0.808888499	0.80966469	0.808652072
GBT	HR	272	250	713	29	22		0.896057348	0.919117647	0.907441016
	LR	406	337	561	47	69		0.877604	0.830049261	0.853164557
	MR	336	278	605	73	58		0.792023	0.827380952	0.809315866
	Total	1014	865	1879	149	149	Overall →	0.853057	0.853057	0.853057
							Weighted →	0.854195807	0.85305720	0.853194179
KNN	HR	272	243	695	47	29		0.837931034	0.893382353	0.864768683
	LR	406	309	525	83	97		0.788265306	0.761083744	0.77443609
	MR	336	241	587	91	95		0.725903614	0.717261905	0.721557
	Total	1014	793	1807	221	221	Overall →	0.782051282	0.782051282	0.782051282
							Weighted →	0.780923639	0.78205128	0.781145215

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