Research Article
Efficient Model Selection for Sparse Least-Square SVMs
Table 8
Training time (in CPU seconds) of FLSA-SVMS, RFLSA-SVMS, SVMs, and LS-SVMs on ringnorm benchmark.
| | FLSA-SVMs | RFLSA-SVMs | log2() | SVMs | LS-SVMs λ = 0.1192 | | λ = 2−5 | λ = 2−5 | λ = 2−5 | SMO | CG |
| | 1 | 7.0310 | 0.0150 | | 5.9840 | 2.5620 | 8.1861 | | 150 | 235.1560 | 2.1250 | | 6.0000 | 2.5470 | 8.4898 | | 300 | 228.1410 | 16.5630 | | 5.9840 | 2.5630 | 9.1043 | | 450 | 219.4060 | 13.5160 | | 5.9690 | 2.5620 | 9.7888 | | 600 | 210.4220 | 36.3430 | | 5.9840 | 2.5620 | 10.5138 | | 750 | 199.8600 | 23.6100 | | 5.9690 | 2.5160 | 11.8843 | | 900 | 189.3440 | 29.1720 | | 6.3280 | 2.5310 | 13.8879 | | 1050 | 179.0150 | 67.1560 | | 5.8590 | 2.4690 | 16.5239 | | 1200 | 167.9220 | 41.3430 | | 5.2190 | 2.4060 | 20.5536 | | 1350 | 156.5000 | 62.6090 | | 5.1100 | 2.3590 | 25.7184 | | 1500 | 143.8430 | 63.1100 | | 5.0150 | 2.4070 | 32.0827 | | 1650 | 131.2180 | 83.4070 | | 5.0160 | 2.3600 | 38.5026 | | 1800 | 119.0470 | 82.5930 | | 5.0160 | 2.3290 | 48.0788 | | 1950 | 105.7820 | 85.5470 | | 5.0000 | 2.3910 | 62.9366 | | 2100 | 92.4840 | 136.6720 | | 5.0160 | 2.3430 | 77.4289 | | 2250 | 78.6570 | 107.9530 | | 5.0310 | 1.9530 | 92.2615 | | 2400 | 65.0000 | 105.4850 | | 5.0310 | 1.8130 | 111.8921 | | 2550 | 50.7500 | 133.1870 | | 5.0310 | 1.7970 | 124.1563 | | 2700 | 36.6560 | 142.8280 | | 5.0150 | 1.8120 | 131.0737 | | 2850 | 22.2180 | 149.6720 | | 5.0310 | 1.7970 | 135.9099 | | 3000 | 7.7030 | 170.1560 | | 5.0150 | 1.8290 | 138.8800 |
| | = 150 | 242.1870 | 2.1400 | | NA | NA | NA | | = 300 | 470.3280 | 18.7030 | | NA | NA | NA | | = 3000 | 2646.1550 | 1553.0620 | | 113.6230 | 47.9080 | 1127.8540 |
|
|
