The results of 5-fold cross-validation of the VINIP models trained by the individual feature
| Classifier . | Feature . | Sensitivity (%) . | Specificity (%) . | Accuracy (%) . | B.Accuracya (%) . | MCC . |
|---|---|---|---|---|---|---|
| SVM | AAC | 74.91 ± 0.0152 | 76.53 ± 0.0137 | 76.29 ± 0.0123 | 75.72 ± 0.0111 | 0.39 ± 0.0197 |
| N5AAC | 73.27 ± 0.0246 | 76.06 ± 0.0153 | 75.65 ± 0.0137 | 74.67 ± 0.0149 | 0.38 ± 0.0243 | |
| C5AAC | 74.18 ± 0.0189 | 75.81 ± 0.0123 | 75.57 ± 0.0098 | 75.00 ± 0.0092 | 0.38 ± 0.0147 | |
| DPC | 84.55 ± 0.0241 | 87.84 ± 0.0034 | 87.36 ± 0.0047 | 86.19 ± 0.0122 | 0.61 ± 0.0180 | |
| C1SAAP | 82.73 ± 0.0249 | 86.47 ± 0.0070 | 85.92 ± 0.0057 | 84.60 ± 0.0116 | 0.58 ± 0.0168 | |
| C2SAAP | 81.09 ± 0.0217 | 83.50 ± 0.0092 | 83.15 ± 0.0103 | 82.30 ± 0.0145 | 0.52 ± 0.0257 | |
| C3SAAP | 84.00 ± 0.0228 | 86.78 ± 0.0132 | 86.37 ± 0.0100 | 85.39 ± 0.0098 | 0.59 ± 0.0186 | |
| RF | AAC | 87.27 ± 0.0144 | 84.91 ± 0.0085 | 85.25 ± 0.0086 | 86.09 ± 0.0102 | 0.58 ± 0.0199 |
| N5AAC | 73.64 ± 0.0232 | 74.53 ± 0.0126 | 74.40 ± 0.0119 | 74.08 ± 0.0142 | 0.36 ± 0.0228 | |
| C5AAC | 73.45 ± 0.0100 | 74.38 ± 0.0093 | 74.24 ± 0.0079 | 73.91 ± 0.0063 | 0.36 ± 0.0108 | |
| DPC | 87.27 ± 0.0129 | 84.28 ± 0.0070 | 84.72 ± 0.0061 | 85.78 ± 0.0070 | 0.58 ± 0.0127 | |
| C1SAAP | 85.27 ± 0.0076 | 82.81 ± 0.0055 | 83.17 ± 0.0043 | 84.04 ± 0.0034 | 0.54 ± 0.0065 | |
| C2SAAP | 82.18 ± 0.0138 | 82.38 ± 0.0013 | 82.35 ± 0.0029 | 82.28 ± 0.0074 | 0.51 ± 0.0111 | |
| C3SAAP | 85.64 ± 0.0149 | 84.88 ± 0.0064 | 84.99 ± 0.0066 | 85.26 ± 0.0092 | 0.57 ± 0.0167 |
| Classifier . | Feature . | Sensitivity (%) . | Specificity (%) . | Accuracy (%) . | B.Accuracya (%) . | MCC . |
|---|---|---|---|---|---|---|
| SVM | AAC | 74.91 ± 0.0152 | 76.53 ± 0.0137 | 76.29 ± 0.0123 | 75.72 ± 0.0111 | 0.39 ± 0.0197 |
| N5AAC | 73.27 ± 0.0246 | 76.06 ± 0.0153 | 75.65 ± 0.0137 | 74.67 ± 0.0149 | 0.38 ± 0.0243 | |
| C5AAC | 74.18 ± 0.0189 | 75.81 ± 0.0123 | 75.57 ± 0.0098 | 75.00 ± 0.0092 | 0.38 ± 0.0147 | |
| DPC | 84.55 ± 0.0241 | 87.84 ± 0.0034 | 87.36 ± 0.0047 | 86.19 ± 0.0122 | 0.61 ± 0.0180 | |
| C1SAAP | 82.73 ± 0.0249 | 86.47 ± 0.0070 | 85.92 ± 0.0057 | 84.60 ± 0.0116 | 0.58 ± 0.0168 | |
| C2SAAP | 81.09 ± 0.0217 | 83.50 ± 0.0092 | 83.15 ± 0.0103 | 82.30 ± 0.0145 | 0.52 ± 0.0257 | |
| C3SAAP | 84.00 ± 0.0228 | 86.78 ± 0.0132 | 86.37 ± 0.0100 | 85.39 ± 0.0098 | 0.59 ± 0.0186 | |
| RF | AAC | 87.27 ± 0.0144 | 84.91 ± 0.0085 | 85.25 ± 0.0086 | 86.09 ± 0.0102 | 0.58 ± 0.0199 |
| N5AAC | 73.64 ± 0.0232 | 74.53 ± 0.0126 | 74.40 ± 0.0119 | 74.08 ± 0.0142 | 0.36 ± 0.0228 | |
| C5AAC | 73.45 ± 0.0100 | 74.38 ± 0.0093 | 74.24 ± 0.0079 | 73.91 ± 0.0063 | 0.36 ± 0.0108 | |
| DPC | 87.27 ± 0.0129 | 84.28 ± 0.0070 | 84.72 ± 0.0061 | 85.78 ± 0.0070 | 0.58 ± 0.0127 | |
| C1SAAP | 85.27 ± 0.0076 | 82.81 ± 0.0055 | 83.17 ± 0.0043 | 84.04 ± 0.0034 | 0.54 ± 0.0065 | |
| C2SAAP | 82.18 ± 0.0138 | 82.38 ± 0.0013 | 82.35 ± 0.0029 | 82.28 ± 0.0074 | 0.51 ± 0.0111 | |
| C3SAAP | 85.64 ± 0.0149 | 84.88 ± 0.0064 | 84.99 ± 0.0066 | 85.26 ± 0.0092 | 0.57 ± 0.0167 |
aB.Accuracy, balanced accuracy. The values represent the mean and standard deviation of all measurements.
The results of 5-fold cross-validation of the VINIP models trained by the individual feature
| Classifier . | Feature . | Sensitivity (%) . | Specificity (%) . | Accuracy (%) . | B.Accuracya (%) . | MCC . |
|---|---|---|---|---|---|---|
| SVM | AAC | 74.91 ± 0.0152 | 76.53 ± 0.0137 | 76.29 ± 0.0123 | 75.72 ± 0.0111 | 0.39 ± 0.0197 |
| N5AAC | 73.27 ± 0.0246 | 76.06 ± 0.0153 | 75.65 ± 0.0137 | 74.67 ± 0.0149 | 0.38 ± 0.0243 | |
| C5AAC | 74.18 ± 0.0189 | 75.81 ± 0.0123 | 75.57 ± 0.0098 | 75.00 ± 0.0092 | 0.38 ± 0.0147 | |
| DPC | 84.55 ± 0.0241 | 87.84 ± 0.0034 | 87.36 ± 0.0047 | 86.19 ± 0.0122 | 0.61 ± 0.0180 | |
| C1SAAP | 82.73 ± 0.0249 | 86.47 ± 0.0070 | 85.92 ± 0.0057 | 84.60 ± 0.0116 | 0.58 ± 0.0168 | |
| C2SAAP | 81.09 ± 0.0217 | 83.50 ± 0.0092 | 83.15 ± 0.0103 | 82.30 ± 0.0145 | 0.52 ± 0.0257 | |
| C3SAAP | 84.00 ± 0.0228 | 86.78 ± 0.0132 | 86.37 ± 0.0100 | 85.39 ± 0.0098 | 0.59 ± 0.0186 | |
| RF | AAC | 87.27 ± 0.0144 | 84.91 ± 0.0085 | 85.25 ± 0.0086 | 86.09 ± 0.0102 | 0.58 ± 0.0199 |
| N5AAC | 73.64 ± 0.0232 | 74.53 ± 0.0126 | 74.40 ± 0.0119 | 74.08 ± 0.0142 | 0.36 ± 0.0228 | |
| C5AAC | 73.45 ± 0.0100 | 74.38 ± 0.0093 | 74.24 ± 0.0079 | 73.91 ± 0.0063 | 0.36 ± 0.0108 | |
| DPC | 87.27 ± 0.0129 | 84.28 ± 0.0070 | 84.72 ± 0.0061 | 85.78 ± 0.0070 | 0.58 ± 0.0127 | |
| C1SAAP | 85.27 ± 0.0076 | 82.81 ± 0.0055 | 83.17 ± 0.0043 | 84.04 ± 0.0034 | 0.54 ± 0.0065 | |
| C2SAAP | 82.18 ± 0.0138 | 82.38 ± 0.0013 | 82.35 ± 0.0029 | 82.28 ± 0.0074 | 0.51 ± 0.0111 | |
| C3SAAP | 85.64 ± 0.0149 | 84.88 ± 0.0064 | 84.99 ± 0.0066 | 85.26 ± 0.0092 | 0.57 ± 0.0167 |
| Classifier . | Feature . | Sensitivity (%) . | Specificity (%) . | Accuracy (%) . | B.Accuracya (%) . | MCC . |
|---|---|---|---|---|---|---|
| SVM | AAC | 74.91 ± 0.0152 | 76.53 ± 0.0137 | 76.29 ± 0.0123 | 75.72 ± 0.0111 | 0.39 ± 0.0197 |
| N5AAC | 73.27 ± 0.0246 | 76.06 ± 0.0153 | 75.65 ± 0.0137 | 74.67 ± 0.0149 | 0.38 ± 0.0243 | |
| C5AAC | 74.18 ± 0.0189 | 75.81 ± 0.0123 | 75.57 ± 0.0098 | 75.00 ± 0.0092 | 0.38 ± 0.0147 | |
| DPC | 84.55 ± 0.0241 | 87.84 ± 0.0034 | 87.36 ± 0.0047 | 86.19 ± 0.0122 | 0.61 ± 0.0180 | |
| C1SAAP | 82.73 ± 0.0249 | 86.47 ± 0.0070 | 85.92 ± 0.0057 | 84.60 ± 0.0116 | 0.58 ± 0.0168 | |
| C2SAAP | 81.09 ± 0.0217 | 83.50 ± 0.0092 | 83.15 ± 0.0103 | 82.30 ± 0.0145 | 0.52 ± 0.0257 | |
| C3SAAP | 84.00 ± 0.0228 | 86.78 ± 0.0132 | 86.37 ± 0.0100 | 85.39 ± 0.0098 | 0.59 ± 0.0186 | |
| RF | AAC | 87.27 ± 0.0144 | 84.91 ± 0.0085 | 85.25 ± 0.0086 | 86.09 ± 0.0102 | 0.58 ± 0.0199 |
| N5AAC | 73.64 ± 0.0232 | 74.53 ± 0.0126 | 74.40 ± 0.0119 | 74.08 ± 0.0142 | 0.36 ± 0.0228 | |
| C5AAC | 73.45 ± 0.0100 | 74.38 ± 0.0093 | 74.24 ± 0.0079 | 73.91 ± 0.0063 | 0.36 ± 0.0108 | |
| DPC | 87.27 ± 0.0129 | 84.28 ± 0.0070 | 84.72 ± 0.0061 | 85.78 ± 0.0070 | 0.58 ± 0.0127 | |
| C1SAAP | 85.27 ± 0.0076 | 82.81 ± 0.0055 | 83.17 ± 0.0043 | 84.04 ± 0.0034 | 0.54 ± 0.0065 | |
| C2SAAP | 82.18 ± 0.0138 | 82.38 ± 0.0013 | 82.35 ± 0.0029 | 82.28 ± 0.0074 | 0.51 ± 0.0111 | |
| C3SAAP | 85.64 ± 0.0149 | 84.88 ± 0.0064 | 84.99 ± 0.0066 | 85.26 ± 0.0092 | 0.57 ± 0.0167 |
aB.Accuracy, balanced accuracy. The values represent the mean and standard deviation of all measurements.
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