Neighborhood Hypergraph Based Classification Algorithm for Incomplete Information System

Table 7

The accuracy of data sets whether missing values exist or not (in: incomplete).

Number	Data set	C4.5	SVM	NaiveBayes	NN	Rough	HyperGraph
1	Blood	0.778	0.762	0.754	0.749	0.480	0.772
2	(in)Blood	0.775	0.762	0.751	0.721	0.600	0.765
3	Balance	0.645	0.902	0.914	0.838	0.698	0.860
4	(in)Balance	0.653	0.878	0.890	0.819	0.635	0.861
5	ILPD	0.684	0.714	0.557	0.645	0.356	0.710
6	(in)ILPD	0.703	0.714	0.559	0.638	0.310	0.705
7	Haberman	0.719	0.735	0.748	0.703	0.387	0.751
8	(in)Haberman	0.722	0.735	0.748	0.680	0.548	0.752
9	Statlog Heart	0.767	0.830	0.848	0.811	0.111	0.852
10	(in)Statlog Heart	0.762	0.810	0.829	0.795	0.259	0.843
11	Spect Heart	0.708	0.727	0.685	0.704	0.704	0.721
12	(in)Spect Heart	0.809	0.824	0.794	0.764	0.556	0.841
13	Bankruptcy	0.980	0.996	0.992	0.996	0.996	0.996
14	(in)Bankruptcy	0.972	0.988	0.992	0.996	0.998	0.996
15	Sonar	0.712	0.760	0.678	0.861	0.619	0.814
16	(in)Sonar	0.755	0.764	0.678	0.760	0.429	0.792
17	Iris	0.960	0.960	0.960	0.953	0.667	0.953
18	(in)Iris	0.913	0.927	0.953	0.880	0.933	0.960
19	Fertility	0.870	0.880	0.880	0.820	0.800	0.880
20	(in)Fertility	0.880	0.880	0.880	0.820	0.800	0.880
21	Lenses	0.833	0.708	0.708	0.792	0.667	0.750
22	(in)Lenses	0.750	0.583	0.667	0.667	0.667	0.733