Table 3.
Classifiers | SLN metastasis | Training set | Validation set | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
ACC | SEN | SPE | AUC | MSE | ACC | SEN | SPE | AUC | MSE | ||
SVM | Positive | 0.76 | 0.75 | 0.76 | 0.82 | 0.20 | 0.85 | 0.71 | 1 | 0.83 | 0.26 |
Negative | 0.76 | 0.75 | 1 | 0.71 | |||||||
XGboost | Positive | 0.84 | 0.89 | 0.76 | 0.92 | 0.17 | 0.85 | 0.86 | 0.83 | 0.83 | 0.34 |
Negative | 0.76 | 0.89 | 0.83 | 0.86 | |||||||
LR | Positive | 0.71 | 0.71 | 0.71 | 0.82 | 0.20 | 0.77 | 0.71 | 0.83 | 0.88 | 0.28 |
Negative | 0.71 | 0.71 | 0.83 | 0.71 |
SVM, support vector machine; LR, logistic regression; ACC, accuracy; SEN, sensitivity; SPE, specificity; AUC, area under the curve; MSE, mean squared error; SLN, sentinel lymph node.