A Novel Algorithm for Imbalance Data Classification Based on Neighborhood Hypergraph

Table 4

Recall.

Dataset	SVM	CS-EN-HN	SMOTE + C4.5	SMOTE-RSB* + C4.5	NRSBoundary-SMOTE + C4.5	N-HyperGraph
Bupa	0.0413	0.7856	0.6483	0.5310	0.6621	0.8405
Colic	0.1764	0.6531	0.7500	0.6912	0.7574	1.0000
Reprocessed	0.0000	0.5999	0.6698	0.6509	0.6320	1.0000
Machine	0.0000	0.8404	8919	0.8514	0.8919	0.9732
Labor	0.8000	0.5000	0.5000	0.7000	0.8000	0.9000
Tic	0.6536	1.0000	0.7711	0.7680	0.7319	1.0000
Iris	0.9800	0.5000	0.9600	0.9400	0.9600	1.0000
Seed	0.9428	0.9428	0.9714	0.9714	0.9714	1.0000
Vc	0.0000	0.9500	0.7700	0.6400	0.7900	1.0000
Glass	0.6323	0.9790	0.7647	0.6764	0.7647	0.9000
Haberman	0.0246	0.7732	0.5185	0.3457	0.5926	1.0000
Transfusion	0.1011	0.9117	0.4775	0.3989	0.5000	1.0000
Abalone (7 : 15)	0.6407	1.0000	0.8447	0.8155	0.7864	1.0000
Balance-scale	0.0000	0.5500	0.0000	0.0000	0.0000	1.0000
Abalone (9 : 18)	0.0000	0.8666	0.3571	0.4347	0.3809	1.0000
Yeast (POX : CTY)	0.1372	0.8000	0.4500	0.4751	0.8039	1.0000
Car	0.0145	1.0000	0.7246	0.7246	0.6956	1.0000
Yeast (ME2 : others)	0.0000	0.8700	0.3529	0.3137	0.4118	1.0000
Average	0.2858	0.8068	0.6346	0.6071	0.6740	0.9785

= 0.001 to 0.6.