核化的多视角特权协同随机矢量功能链接网络及其增量学习方法
|
吴天宇, 王士同
|
Kernel Multi⁃view Privileged Random vector functional link net⁃work and its incremental learning method
|
Tianyu Wu, Shitong Wang
|
|
表2 KMPRVFL和对比算法在NUS?wide数据集上的性能
|
Table 2 Binary classification performance of KMPRVFL and other algorithms on NUS?wide dataset
|
|
| Datasets?A | Datasets?B | KMPRVFL | KRVFL | MED?2C | PSVM?2V |
---|
Accuracy | STD | Accuracy | STD | Accuracy | STD | Accuracy | STD |
---|
| Average | 84.00% | 0.023 | 77.63% | 0.018 | 78.23% | 0.221 | 79.66% | 0.024 | 1 | buildings | computer | 83.86% | 0.021 | 71.93% | 0.015 | 77.17% | 0.015 | 78.36% | 0.012 | 2 | buildings | elk | 86.57% | 0.022 | 81.01% | 0.017 | 81.04% | 0.017 | 82.23% | 0.015 | 3 | buildings | fox | 90.64% | 0.013 | 82.28% | 0.035 | 83.41% | 0.035 | 84.30% | 0.029 | 4 | buildings | horses | 85.35% | 0.030 | 76.42% | 0.011 | 78.87% | 0.011 | 79.82% | 0.015 | 5 | buildings | moon | 83.59% | 0.023 | 75.16% | 0.009 | 81.65% | 0.009 | 78.52% | 0.020 | 6 | buildings | plants | 85.98% | 0.015 | 79.19% | 0.013 | 81.34% | 0.013 | 82.25% | 0.007 | 7 | buildings | road | 72.68% | 0.013 | 63.93% | 0.026 | 62.08% | 0.026 | 65.22% | 0.027 | 8 | computer | elk | 86.12% | 0.033 | 77.21% | 0.025 | 77.47% | 0.025 | 78.66% | 0.025 | 9 | computer | fox | 85.41% | 0.031 | 76.39% | 0.030 | 75.18% | 0.030 | 76.92% | 0.024 | 10 | computer | horses | 89.04% | 0.022 | 78.11% | 0.012 | 81.52% | 0.012 | 82.90% | 0.016 | 11 | computer | moon | 83.10% | 0.028 | 76.45% | 0.026 | 74.64% | 0.026 | 77.99% | 0.029 | 12 | computer | plants | 87.00% | 0.012 | 80.68% | 0.014 | 79.90% | 0.014 | 81.34% | 0.013 | 13 | computer | road | 81.36% | 0.021 | 74.51% | 0.034 | 70.62% | 0.034 | 76.17% | 0.033 | 14 | elk | fox | 75.45% | 0.030 | 68.95% | 0.023 | 68.57% | 0.023 | 70.65% | 0.026 | 15 | elk | horses | 78.88% | 0.021 | 76.67% | 0.023 | 75.73% | 0.023 | 76.74% | 0.024 | 16 | elk | moon | 87.77% | 0.029 | 82.68% | 0.013 | 83.98% | 0.013 | 84.53% | 0.025 | 17 | elk | plants | 84.77% | 0.033 | 82.21% | 0.009 | 83.75% | 0.009 | 83.09% | 0.012 | 18 | elk | road | 82.60% | 0.022 | 78.90% | 0.032 | 79.24% | 0.032 | 79.28% | 0.032 | 19 | fox | horses | 83.80% | 0.021 | 76.65% | 0.018 | 77.68% | 0.018 | 79.99% | 0.019 | 20 | fox | moon | 86.22% | 0.023 | 81.94% | 0.044 | 82.25% | 0.044 | 83.92% | 0.045 | 21 | fox | plants | 79.83% | 0.057 | 79.73% | 0.014 | 73.88% | 0.014 | 82.31% | 0.004 | 22 | fox | road | 84.16% | 0.033 | 78.81% | 0.033 | 81.67% | 0.033 | 79.65% | 0.031 | 23 | horses | moon | 88.18% | 0.033 | 82.56% | 0.028 | 83.76% | 0.028 | 84.59% | 0.032 | 24 | horses | plants | 89.15% | 0.011 | 85.05% | 0.012 | 85.12% | 0.012 | 86.73% | 0.015 | 25 | horses | road | 80.14% | 0.012 | 73.94% | 0.035 | 74.57% | 0.035 | 75.67% | 0.039 | 26 | moon | plants | 86.90% | 0.028 | 81.11% | 0.033 | 82.40% | 0.033 | 83.03% | 0.027 | 27 | moon | road | 81.34% | 0.027 | 74.71% | 0.015 | 75.23% | 0.015 | 76.67% | 0.029 | 28 | plants | road | 82.13% | 0.017 | 76.43% | 0.031 | 77.68% | 0.030 | 78.97% | 0.030 |
|
|
|