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

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