Research Article
Quasiconformal Mapping Kernel Machine Learning-Based Intelligent Hyperspectral Data Classification for Internet Information Retrieval
Table 1
Performance on the Indian Pines data (%).
| Class | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
| SVC (polynomial) | 49.32 | 58.73 | 96.45 | 39.26 | 65.82 | 93.65 | 62.92 | 85.33 | 99.01 | 65.83 | 72.33 | 58.41 | SVC (Gaussian) | 78.02 | 73.65 | 99.16 | 76.92 | 80.52 | 97.12 | 79.78 | 89.80 | 99.79 | 83.64 | 86.04 | 80.74 | KSRC (polynomial) | 51.83 | 59.68 | 96.13 | 49.12 | 78.56 | 93.87 | 62.83 | 84.72 | 98.23 | 67.57 | 75.27 | 60.77 | KSRC (Gaussian) | 77.84 | 76.47 | 99.12 | 75.56 | 79.06 | 97.42 | 82.71 | 88.73 | 98.69 | 83.93 | 86.38 | 81.12 | SVC (-kernel) | 78.32 | 80.49 | 99.97 | 82.55 | 90.25 | 99.29 | 82.70 | 98.57 | 99.89 | 86.85 | 90.26 | 84.46 | QMK (-kernel) | 79.45 | 83.56 | 99.82 | 83.45 | 92.63 | 99.41 | 82.87 | 98.30 | 99.24 | 87.86 | 91.02 | 85.66 |
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