Table 4.
Results of Feature Selection for the S_628 Dataset Using the RF and SVM Methods
| Feature Subset | RF |
SVM |
||||||
|---|---|---|---|---|---|---|---|---|
| Acc (%) | MCC | Sn (%) | Sp (%) | Acc (%) | MCC | Sn (%) | Sp (%) | |
| BPB | 62.58 | 0.25 | 63.69 | 61.46 | 63.06 | 0.27 | 52.87 | 73.25 |
| Kmer (k = 2) | 58.12 | 0.16 | 58.28 | 57.96 | 61.78 | 0.24 | 64.33 | 59.24 |
| Kmer (k = 3) | 60.35 | 0.21 | 62.10 | 58.60 | 61.78 | 0.24 | 66.56 | 57.01 |
| Kmer (k = 4) | 59.71 | 0.19 | 62.74 | 56.69 | 64.97 | 0.30 | 67.52 | 62.42 |
| PC-PseDNC-General (2, 0.11) | 58.76 | 0.18 | 61.78 | 55.73 | 61.15 | 0.22 | 64.01 | 58.28 |
| NCP+ND | 60.83 | 0.22 | 62.74 | 58.92 | 60.99 | 0.22 | 57.01 | 64.97 |
| BPB+Kmer (k = 4) | 64.01 | 0.28 | 64.33 | 63.69 | 68.15 | 0.36 | 66.56 | 69.75 |
| BPB+PC-PseDNC-General (2, 0.11) | 62.90 | 0.26 | 63.38 | 62.42 | 66.08 | 0.33 | 57.64 | 74.52 |
| BPB+NCP+ND | 62.74 | 0.26 | 65.61 | 59.87 | 61.78 | 0.24 | 56.37 | 67.20 |
| BPB+PC-PseDNC-General (2, 0.11) + Kmer(4) | 64.49 | 0.29 | 65.92 | 63.06 | 70.54a | 0.41a | 69.43a | 71.66a |
a
Performance with maximum accuracy.