Skip to main content

Table 2 Accuracy of lip image classification using SVM, WSVM, kNN,MAPLSC and Naive Bayes on the features selected by SVM-RFE (mean ± variance)

From: Computer-assisted lip diagnosis on traditional Chinese medicine using multi-class support vector machines

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