Table 3 Accuracy of lip image classification using SVM, WSVM, kNN, MAPLSC and Naïve Bayes on the features selected by mRMR (mean ± variance)
Lip classes | SVM | WSVM | MAPLSC | Naïve Bayes | kNN |
|---|---|---|---|---|---|
Deep-red | 0.74 ± 0.02 | 0.74 ± 0.02 | 0.72 ± 0.02 | 0.73 ± 0.02 | 0.66 ± 0.02 |
Pale | 0.64 ± 0.21 | 0.67 ± 0.20 | 0.56 ± 0.23 | 0.66 ± 0.20 | 0.59 ± 0.20 |
Purple | 0.86 ± 0.02 | 0.87 ± 0.02 | 0.83 ± 0.02 | 0.85 ± 0.02 | 0.84 ± 0.02 |
Red | 0.87 ± 0.01 | 0.89 ± 0.01 | 0.80 ± 0.02 | 0.87 ± 0.01 | 0.81 ± 0.02 |
TA | 0.81 ± 0.01 | 0.82 ± 0.01 | 0.77 ± 0.01 | 0.81 ± 0.01 | 0.76 ± 0.01 |