From: Enhancing SVM for survival data using local invariances and weighting
 | 10% censoring | 30% censoring | ||||||||||||
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Method | Accuracy | Matthews | NMI | AUC-ROC | Sn | Sp | F1 | Accuracy | Matthews | NMI | AUC-ROC | Sn | Sp | F1 |
Cox model | 0.59 (0.05) | 0.14 (0.15) | 0.04 (0.07) | 0.55 (0.07) | 0.39 (0.05) | 0.51 (0.05) | 0.40 (0.05) | 0.58 (0.06) | 0.11 (0.19) | 0.07 (0.10) | 0.53 (0.07) | 0.39 (0.05) | 0.51 (0.05) | 0.41 (0.04) |
Kernel Cox | 0.61 (0.08) | 0.22 (0.15) | 0.15 (0.17) | 0.64 (0.07) | 0.31 (0.13) | 0.79 (0.02) | 0.46 (0.13) | 0.63 (0.07) | 0.24 (0.15) | 0.07 (0.09) | 0.64 (0.08) | 0.31 (0.13) | 0.79 (0.02) | 0.46 (0.13) |
wSVM-KM | 0.62 (0.04) | 0.08 (0.14) | 0.02 (0.03) | 0.64 (0.07) | 0.29 (0.13) | 0.89 (0.02) | 0.43 (0.13) | 0.59 (0.03) | 0.05 (0.15) | 0.02 (0.01) | 0.64 (0.08) | 0.29 (0.13) | 0.89 (0.02) | 0.43 (0.13) |
wSVM-Prop | 0.60 (0.04) | 0.09 (0.14) | 0.02 (0.03) | 0.64 (0.07) | 0.27 (0.01) | 0.82 (0.02) | 0.42 (0.14) | 0.59 (0.03) | 0.05 (0.15) | 0.02 (0.01) | 0.64 (0.08) | 0.27 (0.01) | 0.82 (0.02) | 0.42 (0.14) |
pSVM-linear-KM | 0.63 (0.07) | 0.23 (0.14) | 0.08 (0.08) | 0.66 (0.09) | 0.72 (0.04) | 0.80 (0.06) | 0.77 (0.05) | 0.61 (0.08) | 0.22 (0.17) | 0.11 (0.09) | 0.66 (0.09) | 0.72 (0.03) | 0.80 (0.06) | 0.78 (0.05) |
pSVM-linear-prop | 0.61 (0.07) | 0.21 (0.14) | 0.07 (0.07) | 0.65 (0.09) | 0.71 (0.04) | 0.75 (0.06) | 0.71 (0.05) | 0.59 (0.09) | 0.17 (0.18) | 0.11 (0.09) | 0.63 (0.09) | 0.71 (0.04) | 0.74 (0.06) | 0.71 (0.05) |
pSVM-radial-KM | 0.63 (0.04) | 0.14 (0.14) | 0.04 (0.09) | 0.63 (0.08) | 0.62 (0.02) | 0.82 (0.04) | 0.69 (0.17) | 0.61 (0.06) | 0.17 (0.16) | 0.10 (0.21) | 0.63 (0.09) | 0.62 (0.02) | 0.82 (0.04) | 0.69 (0.17) |
pSVM-radial-prop | 0.61 (0.04) | 0.14 (0.14) | 0.10 (0.21) | 0.63 (0.08) | 0.59 (0.02) | 0.79 (0.05) | 0.61 (0.14) | 0.56 (0.07) | 0.12 (0.14) | 0.31 (0.36) | 0.63 (0.09) | 0.59 (0.03) | 0.79 (0.03) | 0.61 (0.14) |
LUPI-linear-KM | 0.62 (0.07) | 0.22 (0.15) | 0.07 (0.08) | 0.63 (0.08) | 0.79 (0.04) | 0.69 (0.07) | 0.71 (0.04) | 0.62 (0.07) | 0.18 (0.16) | 0.03 (0.07) | 0.63 (0.09) | 0.79 (0.04) | 0.69 (0.07) | 0.71 (0.04) |
LUPI-linear-prop | 0.61 (0.07) | 0.20 (0.15) | 0.07 (0.08) | 0.63 (0.08) | 0.75 (0.04) | 0.62 (0.07) | 0.64 (0.04) | 0.62 (0.07) | 0.18 (0.16) | 0.03 (0.07) | 0.63 (0.09) | 0.75 (0.04) | 0.62 (0.06) | 0.65 (0.04) |
inSVM-gradient | 0.66 (0.07) | 0.27 (0.14) | 0.06 (0.07) | 0.67 (0.08) | 0.83 (0.03) | 0.81 (0.06) | 0.81 (0.04) | 0.64 (0.07) | 0.27 (0.15) | 0.10 (0.10) | 0.69 (0.09) | 0.83 (0.03) | 0.81 (0.06) | 0.81 (0.04) |
inSVM-averaging | 0.66 (0.07) | 0.28 (0.14) | 0.07 (0.07) | 0.67 (0.09) | 0.81 (0.03) | 0.83 (0.06) | 0.82 (0.04) | 0.65 (0.07) | 0.28 (0.16) | 0.11 (0.11) | 0.68 (0.09) | 0.81 (0.03) | 0.83 (0.06) | 0.83 (0.04) |