Mathematical Problems in Engineering

Research Article

Efficient Model Selection for Sparse Least-Square SVMs

Table 6

Training time (in CPU seconds) of the FLSA-SVM, the RFLSA-SVM, the SVMs, and the LS-SVM on the splice dataset.
FLSA-SVMs RFLSA-SVMs log2( )SVMs LS-SVMs λ = 0.0135
λ = 2−6λ = 2−6λ = 2−7SMO CG
1 1.1400 0.0000 1.0470 0.5000 0.8369
50 3.6100 0.0940 1.0320 0.5310 0.8666
100 3.5780 0.2500 1.0310 0.5150 0.9016
150 3.5150 0.2820 1.0310 0.5160 0.9350
200 3.4530 0.3910 1.0320 0.5000 1.0185
250 3.3750 0.5160 1.0310 0.5000 1.1168
300 3.2820 0.6090 1.0470 0.4690 1.2397
350 3.1560 0.7350 0.9690 0.4530 1.4596
400 3.0160 0.8440 0.8600 0.4380 1.7516
450 2.8750 2.2340 0.7660 0.4060 2.1006
500 2.7040 1.1090 0.7500 0.3750 2.6293
550 2.5150 1.2500 0.7820 0.3750 3.3424
600 2.3120 1.3910 0.8280 0.3590 4.3024
650 2.0930 1.5940 0.9380 0.3280 5.5413
700 1.8440 1.7040 0.9380 0.2970 6.9829
750 1.5940 1.8280 0.9380 0.2970 8.7769
800 1.3120 1.9690 0.9530 0.2970 10.4062
850 1.0310 2.1250 0.9530 0.2970 11.8561
900 0.7040 2.2660 0.9380 0.3120 12.3971
950 0.4060 2.4220 0.9370 0.3120 13.4612
1000 0.0310 2.5940 0.9530 0.3120 13.7259
= 100 8.3280 0.3440  NA NA NA
= 250 18.6710 1.5330  NA NA NA
= 1000 47.5460 26.2070  19.7540 8.3890 105.6486