Table 8.

Results of MCDM with integration of ensemble.

Category	Classifiers	Relative Closeness Scores			Ensemble
		Cm1	Cm2	Cm3	Soft		Hard
					Avg.(Cmj)	Rank	Cm1P	Cm2P	Cm3P	Total(CmjP)	Rank
Asymptomatic	Extra-Trees	1	0.806	0.701	0.835	1	10	10	6	26	2
	SVM	0.478	0.370	0.535	0.461	7	3	4	4	11	8
	RF	0.871	0.683	0.867	0.807	3	8	7	10	25	3
	AdBoost	0.483	0.256	0.422	0.387	9	4	1	3	8	9
	MLP	0.579	0.428	0.614	0.540	5	6	6	5	17	5
	XGBoost	0.690	0.699	0.736	0.708	4	7	8	8	23	4
	GBoost	0.314	0.351	0.807	0.490	6	2	2	9	13	6
	LR	0.267	0.357	0.132	0.252	10	1	3	1	5	10
	k-NN	0.561	0.405	0.262	0.409	8	5	5	2	12	7
	HGBoost	0.920	0.806	0.736	0.821	2	9	10	8	27	1
Symptomatic	Extra-Trees	0.947	0.790	0.772	0.836	1	10	10	8	28	1
	SVM	0.515	0.484	0.647	0.548	8	5	4	4	13	7
	RF	0.717	0.675	0.837	0.743	2	8	8	9	25	2
	AdBoost	0.515	0.427	0.743	0.561	7	5	2	7	14	6
	MLP	0.784	0.643	0.596	0.674	5	9	7	3	19	4
	XGBoost	0.693	0.694	0.672	0.686	3	7	9	6	22	3
	GBoost	0.514	0.626	0.915	0.685	4	3	6	10	19	4
	LR	0.692	0.440	0.589	0.573	6	7	3	2	12	8
	k-NN	0.457	0.511	0.362	0.443	9	2	5	1	8	9
	HGBoost	0.176	0.467	0.662	0.435	10	1	1	5	7	10

-The underlined boldface indicates the highest-ranked models.