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. Author manuscript; available in PMC: 2015 Apr 1.
Published in final edited form as: IEEE Trans Neural Netw Learn Syst. 2015 Mar;26(3):444–457. doi: 10.1109/TNNLS.2014.2315526

Table IV. Total Training and Testing Time (s) of the Different Algorithms.

DATA SVM LGC LapRLS LapSVMp NYS-LGC NFI ANCHOR PVM(SQR) PVM(HINGE)
G241C 0.54 140.84 129.86 33.47 0.86 0.48 11.75 3.30 3.19
G241D 0.55 129.78 142.65 11.95 0.84 0.49 12.33 3.31 3.16
DIGIT1 0.57 140.51 131.08 7.72 0.84 0.48 12.79 3.31 3.15
USPS 0.48 139.23 131.59 21.35 0.74 0.47 12.89 3.28 3.14
COIL2 0.57 151.36 120.48 14.57 0.87 0.48 11.51 3.26 3.47
COIL 1.58 146.92 115.22 31.54 0.79 0.49 13.01 3.35 3.51
BCI 0.08 3.08 1.94 1.12 0.53 0.22 5.89 0.71 1.09
TEXT 25.6 139.67 216.37 59.27 9.14 13.26 47.54 30.24 34.24
SPLICE 1.69 1622.51 1439.51 33.12 2.49 0.83 23.71 4.87 4.24
SEGMENT 4.51 1319.67 1389.80 69.71 1.96 31.67 7.15 6.13 8.81
DNA 2.85 1566.91 1463.75 368.91 3.07 1.22 52.91 8.92 7.57
SVMGD1A 2.71 1129.44 3.22 1.66 69.21 8.06 5.38
USPS-FULL 19.46 8920.13 3.96 2.87 125.70 22.48 28.21
SATIMAGE 8.90 2671.56 3.34 2.57 189.56 11.56 14.32