Table 5.
Molecular subtype classification accuracy of Breast Cancer for the 1046 features
| Normal | LumA | LumB | TNBC | Her2 | Global | |
|---|---|---|---|---|---|---|
| #Samples | 33 | 399 | 139 | 135 | 58 | 764 |
| Gradient Boosting | 0.1818 | 0.9348 | 0.5396 | 0.9333 | 0.5172 | 0.7987 |
| Random Forest | 0.0606 | 0.9724 | 0.4532 | 0.9630 | 0.0345 | 0.7657 |
| Logistic Regression | 0.1212 | 0.8747 | 0.5540 | 0.9259 | 0.4483 | 0.7606 |
| Passive Aggressive | 0.1515 | 0.8622 | 0.5612 | 0.9111 | 0.4483 | 0.7539 |
| SGD | 0.3030 | 0.9073 | 0.4604 | 0.9556 | 0.4655 | 0.7752 |
| SVC | 0.2727 | 0.8797 | 0.5252 | 0.9185 | 0.5345 | 0.7697 |
| Ridge | 0.1515 | 0.7293 | 0.4317 | 0.3704 | 0.2759 | 0.5524 |
| Bagging | 0.3333 | 0.9298 | 0.5108 | 0.9704 | 0.4310 | 0.7973 |
| Average | 0.1970 | 0.8863 | 0.5045 | 0.8685 | 0.3944 | 0.7467 |