Table 2:
Comparison of machine learning methods to classify cancer cells and PDX cancer cells by brain metastatic potential.
| Cancer cells | |||
|---|---|---|---|
| Method | AUC | Accuracy | F1 |
| Neural Network | 0.925 | 0.84 | 0.847 |
| AdaBoost | 0.928 | 0.853 | 0.86 |
| Random Forest | 0.925 | 0.849 | 0.855 |
| Decision Tree | 0.898 | 0.817 | 0.827 |
| kNN | 0.775 | 0.702 | 0.718 |
| Logistic Regression | 0.769 | 0.735 | 0.751 |
| Naive Bayes | 0.745 | 0.715 | 0.73 |
| SGD | 0.73 | 0.73 | 0.737 |
| PDX Cancer cells | |||
| Method | AUC | CA | F1 |
| Neural Network | 0.972 | 0.881 | 0.878 |
| Random Forest | 0.964 | 0.888 | 0.887 |
| AdaBoost | 0.957 | 0.881 | 0.879 |
| Tree | 0.954 | 0.867 | 0.865 |
| Logistic Regression | 0.897 | 0.832 | 0.831 |
| Naive Bayes | 0.896 | 0.846 | 0.849 |
| kNN | 0.882 | 0.818 | 0.814 |
| SGD | 0.861 | 0.86 | 0.853 |