Table 2.
Average performance of eight supervised machine learning algorithms
| Area under the ROC curve | Replicate correlation | |||
|---|---|---|---|---|
| RS | CV | FNA | ||
| Diagonal linear discriminant analysis | 0.89 | 0.89 | 0.94 | 0.98 |
| k‐nearest neighbours | 0.95 | 0.89 | 0.88 | 0.97 |
| Logistic regression | 0.92 | 0.90 | 0.91 | 0.97 |
| Neural network | 0.94 | 0.86 | 0.85 | 0.92 |
| Quadratic discriminant analysis | 0.93 | 0.88 | 0.87 | 0.96 |
| Random forest | 1.00 | 0.89 | 0.89 | 0.95 |
| Support vector machine, linear kernel | 0.91 | 0.89 | 0.89 | 0.96 |
| Support vector machine, radial kernel | 0.97 | 0.88 | 0.85 | 0.95 |
ROC, receiver operating characteristic; RS, resubstitution in training set; CV, cross‐validation in training set; FNA, fine‐needle aspiration test set.