Table 3 Support Vector Machine and Random forest CV accuracy
From: A machine learning approach for early identification of patients with severe imported malaria
Support Vector Machine (RBF) CV accuracy | Random Forest CV accuracy | |
|---|---|---|
With WHO criteria | 90.3% | 86.9% |
With no WHO criteria | 81.9% | 84.6% |