Research Article
Predictions of Apoptosis Proteins by Integrating Different Features Based on Improving Pseudo-Position-Specific Scoring Matrix
Table 6
Performance comparison of different models on the CL317 dataset.
| Methods | Prediction accuracy (%) | Cy | Me | Mi | Se | Nu | En | OA |
| OF-SVM [3] | 94.6 | 90.9 | 76.5 | 92.2 | 86.5 | 93.6 | 89.6 | FTD-SVM [20] | 92.9 | 89.1 | 82.4 | 70.6 | 86.5 | 93.6 | 89.0 | BOW-SVM [6] | 94.6 | 87.3 | 82.4 | 82.4 | 84.3 | 91.5 | 89.2 | GA_DCCA-SVM [36] | 92.9 | 89.1 | 82.4 | 76.5 | 84.6 | 93.6 | 89.0 | OA-SVM [16] | 96.1 | 95.7 | 93.9 | 98.0 | 95.5 | 100 | 96.0 | IACC-SVM [18] | 96.4 | 94.5 | 82.4 | 76.5 | 80.8 | 93.6 | 90.5 | PSSMP [17] | 92.0 | 92.7 | 82.4 | 76.5 | 90.4 | 93.6 | 90.5 | EN-FKNN [37] | 98.2 | 83.6 | 79.4 | 82.4 | 90.4 | 97.9 | 91.5 | OA-MLSC [29] | 95.5 | 93.6 | 96.4 | 94.1 | 94.2 | 94.1 | 94.8 | This paper | 100 | 100 | 100 | 94.69 | 97.03 | 100 | 98.47 |
|
|