Support vector machine with hypergraph-based pairwise constraints

Hou, Qiuling; Lv, Meng; Zhen, Ling; Jing, Ling

doi:10.1186/s40064-016-3315-x

SpringerPlus

Table 2 Test accuracy on UCI datasets for linear classifiers

From: Support vector machine with hypergraph-based pairwise constraints

Datasets	SVM			LSSVM			SRSVM			MPCSVM			HPCSVM
Datasets	Accuracy	Time (s)	p value	Accuracy	Time (s)	p value	Accuracy	Time (s)	p value	Accuracy	Time (s)	p value	Accuracy	Time (s)
Hepatitis (155 × 19)	83.30 ± 6.64	0.06	0.6983	83.99 ± 8.98	0.02	0.8315	84.99 ± 8.25	0.07	0.5145	84.61 ± 7.11	0.09	0.9033	85.24 ± 6.98	0.06
Heartstatlog (270 × 13)	80.00 ± 5.16	0.16	0.2433	84.07 ± 6.04	0.03	0.8072	84.44 ± 5.05	0.21	0.8825	85.19 ± 5.86	0.23		85.19 ± 6.42	0.17
Teaching (151 × 5)	68.85 ± 2.80	0.06	0.2216	72.54 ± 5.36	0.03	0.8757	72.94 ± 5.36	0.07	0.8238	72.85 ± 5.31	0.07	0.8596	73.63 ± 6.65	0.05
Haberman (306 × 3)	73.53 ± 0.49	0.25	0.4298	74.50 ± 2.57	0.04	0.7847	75.50 ± 2.57	0.28	0.8765	75.47 ± 3.55	0.26	0.9067	75.15 ± 3.86	0.17
Breast (683 × 9)	96.04 ± 3.68	1.87	0.5185	96.05 ± 1.95	0.22	0.2999	97.19 ± 1.42	2.18	0.9124	97.21 ± 1.88	2.29	0.9009	97.36 ± 1.36	1.59
BUPA (345 × 6)	67.53 ± 3.73	0.30	0.2073	68.70 ± 6.19	0.05	0.5306	69.99 ± 4.55	0.32	0.7536	71.01 ± 4.20	0.34	1	71.01 ± 3.43	0.24
Diabetes (768 × 8)	71.48 ± 2.65	2.54	0.0435	77.61 ± 4.65	0.34	0.8534	75.61 ± 4.65	2.28	0.5216	78.01 ± 3.87	2.40	0.9365	78.27 ± 5.02	1.86
Seeds (210 × 7)	95.24 ± 6.10	0.10	0.0037	97.14 ± 2.78	0.03	0.5796	98.84 ± 2.78	0.12	0.8215	98.10 ± 1.78	0.14	1	98.10 ± 1.78	0.10
Sonar (208 × 60)	72.16 ± 9.52	0.10	0.3209	77.34 ± 8.47	0.02	0.8122	78.34 ± 7.73	0.08	0.9354	79.74 ± 7.56	0.16	0.8664	78.78 ± 8.12	0.10
Parkinsons (195 × 22)	84.09 ± 1.92	0.08	0.0191	88.23 ± 1.03	0.02	0.5307	88.53 ± 1.03	0.14	0.6346	88.27 ± 3.69	0.13	0.6874	89.25 ± 2.96	0.09
Spect (267 × 44)	79.78 ± 0.70	0.25	0.0687	79.40 ± 0.19	0.04	0.0438	82.40 ± 0.19	0.28	0.8765	83.90 ± 3.61	0.27	0.7601	83.14 ± 3.13	0.18
Ionosphere (351 × 33)	87.75 ± 2.33	0.45	0.4902	86.61 ± 1.16	0.07	0.0959	88.86 ± 1.41	0.50	0.9645	90.31 ± 3.32	0.40	0.4913	88.89 ± 2.12	0.28
Heartcancer (303 × 14)	96.33 ± 7.33	0.16	0.3466	92.09 ± 1.89	0.03	0.0000	98.09 ± 1.78	0.25	0.5024	100 ± 0.00	0.29	NaN	100 ± 0.00	0.21
Heart_diseas e(294 × 13)	72.79 ± 6.84	0.27	0.0326	82.33 ± 4.19	0.04	0.6854	83.00 ± 3.82	0.30	0.8456	83.35 ± 5.04	0.26	0.9258	83.69 ± 4.95	0.19
Fertility (100 × 9)	86.29 ± 4.93	0.02	0.3105	88.08 ± 1.94	0.01	0.6001	90.08 ± 1.98	0.04	0.6570	90.18 ± 4.04	0.04	0.6982	89.13 ± 3.34	0.03
Ech_diogram (131 × 10)	87.00 ± 7.04	0.05	0.5075	88.39 ± 6.69	0.03	0.7137	89.39 ± 5.96	0.07	0.9035	89.96 ± 4.83	0.06	1	89.96 ± 4.83	0.05
Balancescale (576 × 4)	95.49 ± 1.77	0.89	0.4746	95.32 ± 2.08	0.17	0.4419	96.49 ± 1.57	1.15	0.9654	96.36 ± 0.83	1.20	0.9986	96.36 ± 1.49	0.83
WPBC (198 × 34)	78.27 ± 5.00	0.10	0.2938	80.36 ± 4.09	0.03	0.5125	82.36 ± 4.67	0.11	0.9941	82.37 ± 4.34	0.14	0.9971	82.38 ± 5.35	0.10
WDBC (569 × 30)	93.51 ± 5.13	0.87	0.0000	96.13 ± 1.89	0.18	0.0994	98.13 ± 2.24	1.13	0.9235	98.07 ± 0.86	1.32	1	98.07 ± 0.86	0.93
Vertebral (310 × 6)	85.48 ± 2.89	0.25	0.4520	85.16 ± 4.26	0.04	0.4731	86.12 ± 4.52	0.30	0.7538	87.10 ± 3.38	0.28	1	87.10 ± 2.89	0.21
Australian (690 × 14)	85.51 ± 1.62	2.49	0.2854	86.09 ± 1.12	0.20	0.4450	86.87 ± 2.15	2.25	0.8856	86.96 ± 1.87	1.89	0.9218	87.11 ± 2.28	1.55
BTSC (748 × 4)	75.55 ± 2.52	2.51	0.0000	77.27 ± 0.68	0.32	0.1793	77.54 ± 1.03	2.28	0.2058	79.28 ± 2.92	2.08	0.8968	79.41 ± 2.82	1.67
Tic_tac_toe (958 × 27)	98.33 ± 0.39	2.20	1	98.33 ± 0.39	0.26	1	98.33 ± 0.39	3.25	1	98.33 ± 0.39	5.79	1	98.33 ± 0.39	3.00
German (1000 × 24)	74.90 ± 2.22	4.27	0.1839	76.80 ± 2.46	0.28	0.6755	77.10 ± 2.62	6.26	0.7640	77.50 ± 1.38	5.21	0.8997	77.70 ± 2.74	4.08
CMC (1473 × 9)	77.39 ± 0.13	11.80	0.0936	77.46 ± 0.52	1.64	0.1467	78.73 ± 0.43	14.03	0.9023	78.07 ± 0.96	12.36	0.6478	78.41 ± 1.06	9.06

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