An Ensemble Learning Method Based on an Evidential Reasoning Rule considering Combination Weighting

Table 5

Comparative study of five datasets.

Dataset	Classifier	Combination weighting method			Comparative method
		EW(rg)AHP	COV(rg)AHP	CRITIC(rg)AHP	RSR-EW	G1
Fish	DIE	0.9605	0.9605	0.9608	0.9608	0.9625
	DIR	0.9465	0.9470	0.9468	0.9468	0.9470
	IER	0.9585	0.9585	0.9585	0.9578	0.9590
	MIE	0.9610	0.9605	0.9603	0.9608	0.9603
	MIR	0.9565	0.9565	0.9568	0.9533	0.9563
Weather	DIE	0.9727	0.9727	0.9727	0.9719	0.9724
	DIR	0.9835	0.9838	0.9838	0.9830	0.9838
	IER	0.9869	0.9869	0.9869	0.9866	0.9869
	MIE	0.9753	0.9753	0.9750	0.9742	0.9750
	MIR	0.9851	0.9845	0.9845	0.9835	0.9845
Flower	DIE	0.8337	0.8331	0.8334	0.8331	0.8346
	DIR	0.8306	0.8309	0.8309	0.8275	0.8301
	IER	0.8438	0.8433	0.8438	0.8410	0.8433
	MIE	0.8500	0.8500	0.8500	0.8512	0.8401
	MIR	0.8410	0.8416	0.8419	0.8376	0.8410
Fruit	DIE	0.8123	0.8103	0.8098	0.8041	0.8093
	DIR	0.8555	0.8591	0.8586	0.8504	0.8612
	IER	0.8581	0.8602	0.8603	0.8581	0.8658
	MIE	0.8175	0.8195	0.8180	0.8149	0.8201
	MIR	0.8715	0.8766	0.8807	0.8823	0.8828
Dog	DIE	0.8764	0.8764	0.8795	0.8811	0.8842
	DIR	&	&	&	&	&
	IER	0.8905	0.8889	0.8873	0.8936	0.8842
	MIE	0.8858	0.8873	0.8920	0.8842	0.8889
	MIR	0.8920	0.8920	0.8936	0.8905	0.8936