Table 2 Accuracy of lip image classification using SVM, WSVM, kNN,MAPLSC and Naive Bayes on the features selected by SVM-RFE (mean ± variance)
Lip classes | SVM | WSVM | MAPLSC | Naïve Bayes | kNN |
|---|---|---|---|---|---|
Deep-red | 0.81 ± 0.02 | 0.72 ± 0.02 | 0.69 ± 0.02 | 0.72 ± 0.03 | 0.72 ± 0.02 |
Pale | 0.71 ± 0.16 | 0.65 ± 0.21 | 0.70 ± 0.22 | 0.67 ± 0.20 | 0.43 ± 0.22 |
Purple | 0.89 ± 0.02 | 0.88 ± 0.02 | 0.90 ± 0.01 | 0.85 ± 0.02 | 0.88 ± 0.02 |
Red | 0.86 ± 0.01 | 0.86 ± 0.01 | 0.82 ± 0.02 | 0.88 ± 0.02 | 0.78 ± 0.02 |
TA | 0.84 ± 0.01 | 0.81 ± 0.01 | 0.79 ± 0.01 | 0.81 ± 0.05 | 0.77 ± 0.01 |