A Novel Ensemble Credit Scoring Model Based on Extreme Learning Machine and Generalized Fuzzy Soft Sets

Table 8

Comparison results of ensemble models in different data sets.

Data set	Performance measurement	Ensemble models
		EMPNGA-based model	Heterogeneous ensemble	EBCA-RF& XGB-PSO	TSHE	TNN	RKE	EGHE
Germany	AUC	0.802	0.795	0.798	0.775	0.811	0.790	0.823
	HM	0.400	0.386	0.397	0.376	0.320	0.376	0.325
	BS	0.158	0.164	0.163	0.184	0.181	0.158	0.184
	ACC	0.768	0.859	0.869	0.839	0.873	0.874	0.886
Australia	AUC	0.940	0.923	0.931	0.933	0.931	0.929	0.945
	HM	0.672	0.648	0.661	0.628	0.649	0.676	0.659
	BS	0.092	0.101	0.092	0.101	0.095	0.099	0.096
	ACC	0.875	0.842	0.861	0.852	0.882	0.877	0.895
Japan	AUC	0.932	0.925	0.919	0.935	0.923	0.921	0.937
	HM	0.665	0.651	0.636	0.649	0.650	0.649	0.660
	BS	0.095	0.091	0.097	0.090	0.097	0.090	0.098
	ACC	0.872	0.883	0.889	0.887	0.890	0.887	0.904
Iran	AUC	0.876	0.824	0.831	0.824	0.790	0.821	0.802
	HM	0.424	0.384	0.489	0.384	0.298	0.416	0.303
	BS	0.058	0.047	0.061	0.043	0.058	0.053	0.059
	ACC	0.907	0.908	0.921	0.902	0.911	0.910	0.915
Bene 1	AUC	0.824	0.821	0.818	0.821	0.868	0.819	0.881
	HM	0.376	0.383	0.442	0.423	0.346	0.384	0.351
	BS	0.152	0.147	0.147	0.150	0.169	0.139	0.173
	ACC	0.872	0.869	0.869	0.865	0.883	0.872	0.896
Bene 2	AUC	0.866	0.871	0.863	0.881	0.874	0.875	0.887
	HM	0.479	0.488	0.465	0.498	0.498	0.490	0.506
	BS	0.102	0.098	0.101	0.118	0.112	0.110	0.114
	ACC	0.871	0.867	0.875	0.887	0.885	0.882	0.898
Shuttle	AUC	0.913	0.870	0.850	0.865	0.929	0.850	0.943
	HM	0.442	0.405	0.500	0.403	0.648	0.431	0.658
	BS	0.060	0.050	0.062	0.045	0.095	0.055	0.096
	ACC	0.886	0.878	0.892	0.886	0.902	0.892	0.916
Skin_segment	AUC	0.859	0.867	0.837	0.862	0.921	0.848	0.935
	HM	0.392	0.404	0.452	0.444	0.649	0.397	0.659
	BS	0.158	0.155	0.150	0.158	0.096	0.143	0.098
	ACC	0.870	0.877	0.889	0.898	0.894	0.893	0.908
MiniBooNE	AUC	0.903	0.919	0.883	0.925	0.788	0.906	0.800
	HM	0.499	0.515	0.476	0.523	0.297	0.507	0.302
	BS	0.106	0.103	0.103	0.124	0.058	0.114	0.059
	ACC	0.890	0.895	0.901	0.897	0.889	0.901	0.903
LC2017Q1	AUC	0.858	0.846	0.822	0.923	0.866	0.845	0.879
	HM	0.402	0.274	0.340	0.368	0.345	0.266	0.350
	BS	0.165	0.250	0.258	0.213	0.199	0.202	0.203
	ACC	0.888	0.897	0.903	0.895	0.898	0.903	0.912