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Table 3 Accuracy of lip image classification using SVM, WSVM, kNN, MAPLSC and Naïve Bayes on the features selected by mRMR (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 0.74 ± 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