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Table 1 Accuracy of lip image classification using SVM, WSVM, kNN,MAPLSC and Naive Bayes on all the 84 features (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 0.73 ± 0.02 0.72 ± 0.02 0.71 ± 0.02 0.64 ± 0.02 0.61 ± 0.03
Pale 0.51 ± 0.22 0.57 ± 0.22 0.61 ± 0.22 0.73 ± 0.18 0.34 ± 0.20
Purple 0.85 ± 0.02 0.87 ± 0.02 0.83 ± 0.02 0.84 ± 0.02 0.78 ± 0.03
Red 0.87 ± 0.01 0.93 ± 0.01 0.84 ± 0.01 0.82 ± 0.02 0.81 ± 0.02
TA 0.80 ± 0.01 0.82 ± 0.01 0.78 ± 0.01 0.76 ± 0.01 0.71 ± 0.01