A High Accurate Multiple Classifier System for Entity Resolution Using Resampling and Ensemble Selection

Table 1

Accuracy comparison.

	Dataset	Bagging	DREP	Gentle AdaBoost	REA	RES
Synthetic data	breast cancer	0.8996 ± 0.0002	0.9088 ± 0.0002^●	0.9215 ± 0.0003^●	0.9045 ± 0.0001^●	0.9327 ± 0.0002^●
	innosphere	0.9647 ± 0.0001	0.9732 ± 0^●	0.9946 ± 0.0001^●	0.9832 ± 0^○	0.9911 ± 0^●
	dermatology	0.9541 ± 0.0003	0.9676 ± 0.0002^●	0.9649 ± 0.0002^●	0.9588 ± 0.0001	0.9825 ± 0.0001^●
	ILPD	0.9619 ± 0.0001	0.9721 ± 0^●	0.9964 ± 0^●	0.9579 ± 0.0001^○	0.9929 ± 0.0002^●
	seismic	0.9779 ± 0	0.9756 ± 0^○	0.9984 ± 0^●	0.9878 ± 0^●	0.9942 ± 0^●
	abalone	0.9812 ± 0	0.9812 ± 0.0001	0.9880 ± 0^●	0.9833 ± 0	0.9940 ± 0^●
	vote	0.7592 ± 0.0001	0.7495 ± 0.0005	0.9515 ± 0.0001^●	0.8155 ± 0.0004^●	0.8447 ± 0.0003^●
	biodeg	0.8036 ± 0.0001	0.7643 ± 0.0002^○	0.9643 ± 0.0001^●	0.8155 ± 0.0004^●	0.8214 ± 0.0002^●
	glass	0.9255 ± 0.0002	0.9275 ± 0.0004^●	0.9804 ± 0.0001^●	0.9216 ± 0.0006^○	0.9412 ± 0.0003^●
	diabets	0.9429 ± 0.0002	0.9457 ± 0.0008	0.9837 ± 0^●	0.8891 ± 0.0005^○	0.9457 ± 0
Real data	abt_buy	0.9417 ± 0	0.9444 ± 0^●	0.9372 ± 0.0001^○	0.9465 ± 0^●	0.9535 ± 0^●
	amazon_gp	0.9669 ± 0	0.9640 ± 0^○	0.9525 ± 0.0001^○	0.9729 ± 0^●	0.9796 ± 0^●
	dblp_acm	0.9938 ± 0	0.9975 ± 0^●	0.9994 ± 0^●	0.9966 ± 0^●	0.9966 ± 0^●
	dblp_scholar	0.9809 ± 0	0.9750 ± 0^○	0.9783 ± 0^○	0.9817 ± 0	0.9848 ± 0^●
	cora	0.9407 ± 0.0001	0.9650 ± 0^●	0.9550 ± 0^●	0.9465 ± 0^●	0.9600 ± 0^●
	win/tie/loss		9/2/4	12/0/3	8/3/4	14/1/0