Table 5. Results of the proposed methods (DBI, BRI & BRIX) on the USPS dataset with different reduction ratios.

Ratio	Training Speedup			Testing Speedup			Accuracy			Number of SVs			Jaccard similarity
Whole dataset	1.00			1.00			0.922			790			1.00
	DBI	BRI	BRIX	DBI	BRI	BRIX	DBI	BRI	BRIX	DBI	BRI	BRIX	DBI	BRI	BRIX
0.01	88.81	90.70	98.19	6.24	8.81	9.44	0.488	0.305	0.786	82	58	52	0.08	0.07	0.02
0.02	66.88	64.54	72.90	4.37	5.06	6.77	0.548	0.701	0.896	139	113	80	0.12	0.09	0.04
0.03	58.51	62.66	63.79	3.92	4.22	5.85	0.564	0.802	0.909	178	161	102	0.15	0.10	0.04
0.04	54.48	50.28	62.17	3.29	3.41	5.78	0.622	0.871	0.915	217	199	109	0.18	0.12	0.05
0.05	39.06	45.14	51.77	2.52	3.20	5.12	0.684	0.891	0.917	254	227	123	0.20	0.12	0.05
0.1	24.22	27.71	33.35	1.70	2.38	4.84	0.850	0.917	0.920	405	306	142	0.25	0.15	0.07
0.2	13.03	14.96	18.85	1.79	2.38	4.38	0.911	0.921	0.921	412	309	159	0.29	0.19	0.09
0.3	9.08	9.15	12.87	1.76	2.19	4.15	0.917	0.921	0.921	415	326	179	0.33	0.23	0.12
0.4	6.73	6.57	8.20	1.85	2.16	3.20	0.919	0.921	0.921	421	345	225	0.34	0.26	0.17
0.5	4.99	5.14	6.57	1.80	2.17	3.00	0.920	0.922	0.921	418	362	248	0.35	0.29	0.20
0.6	4.21	4.38	5.05	1.81	2.09	2.77	0.920	0.922	0.922	406	374	272	0.36	0.32	0.23
0.7	3.44	3.31	3.75	1.83	1.90	2.39	0.921	0.922	0.921	403	388	307	0.38	0.35	0.27
0.8	2.72	3.01	2.84	1.78	1.87	2.09	0.921	0.922	0.922	407	397	345	0.39	0.37	0.32
0.9	2.34	2.52	2.37	1.74	1.78	1.97	0.922	0.922	0.922	411	405	383	0.41	0.40	0.38

Each row compares performance metrics of the proposed methods for a different value (0.01 to 0.05 and 0.1 to 0.9) of the reduction ratio parameter r (the user-defined desired proportion of the training set to retain). The first row represents the metrics measured after training on the whole dataset.