From: Predicting factors for survival of breast cancer patients using machine learning techniques
No | Algorithm | Accuracy (%) | Sensitivity | Specificity | AUC | Precision | Matthews correlation coefficient |
---|---|---|---|---|---|---|---|
1 | Decision tree | 79.80 | 0.82 | 0.75 | 0.72 | 0.91 | 0.52 |
2 | Random forest | 82.70 | 0.83 | 0.81 | 0.86 | 0.93 | 0.59 |
3 | Neural networks | 82.00 | 0.83 | 0.79 | 0.84 | 0.93 | 0.58 |
4 | Extreme boost | 81.70 | 0.84 | 0.75 | 0.87 | 0.89 | 0.57 |
5 | Logistic regression | 81.10 | 0.82 | 0.78 | 0.85 | 0.92 | 0.55 |
6 | Support vector machine | 81.80 | 0.81 | 0.84 | 0.85 | 0.95 | 0.57 |