Neighborhood Hypergraph Based Classification Algorithm for Incomplete Information System

Table 2

Accuracy.

No.	Data set	C4.5	SVM	NaiveBayes	NN	Rough (incomplete)	Rough (complete)	HyperGraph
1	Mammographic	0.823	0.817	0.834	0.798	0.680	0.649	0.834
2	Blood	0.775	0.762	0.751	0.721	0.600	0.480	0.765
3	Credit Approval	0.861	0.849	0.777	0.846	0.609	0.217	0.861
4	Balance	0.653	0.878	0.890	0.819	0.635	0.635	0.861
5	ILPD	0.703	0.714	0.559	0.638	0.310	0.069	0.705
6	Haberman	0.722	0.735	0.748	0.680	0.548	0.258	0.752
7	Hungarian	0.810	0.827	0.837	0.769	0.400	0.233	0.845
8	Statlog Heart	0.762	0.810	0.829	0.795	0.259	0.259	0.843
9	Spect Heart	0.809	0.824	0.794	0.764	0.556	0.704	0.841
10	Bankruptcy	0.972	0.988	0.992	0.996	0.998	0.840	0.996
11	Sonar	0.755	0.764	0.678	0.760	0.429	0.715	0.792
12	Iris	0.913	0.927	0.953	0.880	0.933	0.667	0.960
13	Fertility	0.880	0.880	0.880	0.820	0.880	0.500	0.880
14	Postoperative	0.700	0.689	0.678	0.656	0.333	0.556	0.711
15	Lenses	0.750	0.583	0.667	0.667	0.667	0.333	0.733
	Average	0.793	0.803	0.791	0.774	0.584	0.474	0.825