Mathematical Problems in Engineering / 2015 / Article / Tab 6 / Research Article
A Fuzzy Kernel Maximum Margin Criterion for Image Feature Extraction Table 6 The average training times and the average testing times of eleven methods on four face databases: GTFD, Yale B, AR, and FERET for sample numbers per class
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ā GTFD Yale B AR FERET ā Train (s) Test (s) Train (s) Test (s) Train (s) Test (s) Train (s) Test (s) LPP 0.3985 0.00038 0.2104 0.00031 1.5729 0.00077 3.5654 0.0012 TSA 2.1942 0.0031 1.6920 0.0023 4.6643 0.0065 4.7604 0.0079 KPCA 0.4531 0.0042 0.2843 0.0032 6.2557 0.0099 17.0743 0.0113 KLDA 0.5560 0.0042 0.2990 0.0031 6.373 0.0097 17.9793 0.0114 2DLDA 0.0711 0.0007 0.0991 0.00054 0.1917 0.0016 0.1390 0.0027 LLD 0.3056 0.00035 0.2064 0.00028 2.5272 0.00068 10.0023 0.0011 FIFDA 1.0285 0.00058 0.3920 0.00044 10.2263 0.0011 47.3983 0.0016 LBMMC 17.0785 0.0018 8.7614 0.0014 86.9606 0.0040 178.0315 0.0055 2D-MMC 0.1071 0.0010 0.1647 0.00079 0.3161 0.0024 0.2689 0.0037 B2D-MMC 0.2024 0.00084 0.2450 0.00064 0.4989 0.0018 0.6488 0.0029 FKMMC 0.4472 0.0013 0.2574 0.00098 5.4658 0.0033 15.4058 0.0040